Articles for diagnosis of liver fibrosis

ABSTRACT

Disclosed are methods and articles (e.g., gene arrays or antibodies) for determining the progression or regression of liver fibrosis, for the diagnosis of liver disease, and for screening compounds for hepatotoxicity and efficacy against liver fibrosis. Related therapeutic methods also are disclosed.

RELATED APPLICATIONS

This application is a U.S. National Stage Application under 35 U.S.C. § 371 of International Application No. PCT/US2016/015505 filed Jan. 29, 2016, which claims priority to U.S. Provisional Application No. 62/110,058 filed Jan. 30, 2015, the entire contents of which are incorporated by reference herewith.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support and the government has certain rights in the invention.

BACKGROUND OF THE INVENTION

Disclosed herein are methods and articles (e.g., gene arrays or antibodies or qPCR or RNA sequencing) for determining the progression or regression of liver fibrosis, for the diagnosis of liver disease, and for screening compounds for hepatotoxicity and efficacy against liver fibrosis. Related therapeutic methods also are disclosed.

Liver fibrosis is the characteristic pathologic feature of most chronic liver diseases. It is marked by chronic inflammation and excessive accumulation of extracellular matrix (ECM) components. Liver fibrosis is a progressive disease that leads to cirrhosis, portal hypertension, and ultimately results in liver failure. It can also result in hepatocellular carcinoma.

Liver fibrosis is caused by diverse factors such as hepatitis B and hepatitis C virus infection, alcoholism (alcoholic steatohepatitis), obesity (non-alcoholic steatohepatitis), and exposure to toxic chemicals. Such chronic liver diseases are fast becoming a major health problem that affects millions of people worldwide. In 2010, nearly one million deaths globally were attributed to liver cirrhosis. It is estimated that approximately 370 million and 130 million people are infected with hepatitis B and C virus respectively. Every year, nearly 6000 liver transplantations are performed each year in the U.S. and Europe. Estimated costs of cirrhosis and chronic liver disease in the U.S. were approximately $2.5 billion (direct) and $10.6 billion (indirect) in 2004. Since the factors contributing to chronic liver disease are growing in epidemic proportion, this burden is expected to rise significantly over the next 20 years. Currently, there are no approved drugs for the treatment of liver fibrosis.

Liver biopsy is the current gold standard for determining the presence of liver fibrosis. However, liver biopsy is an invasive procedure and requires hospitalization. The use of liver biopsy has a number of limitations such as sampling issues and intra/inter-observer variations. One of the clinically used non-invasive diagnostic tests for liver injury is the FibroSure panel, which is based on a predictive algorithm incorporating age, gender, and blood concentrations of the analytes a2-macroglobulin, haptoglobulin, bilirubin, and apolipoprotein A. Although the panel correlates well with late-stage fibrosis diagnosed by liver biopsy, it lacks sensitivity and specificity as an early (stage 1-2) diagnostic indicator.

There also is a need for improved methodologies for identifying the hepatotoxicity of potential drug candidates. Hepatotoxicity is a common form of toxicity encountered in drug development, and is responsible for the withdrawal of many drugs from the market. Earlier identification of such potential toxic compounds will help to improve the drug discovery process and will save significant amounts of cost and time. For example, the ability to identify compounds that have the propensity to cause liver fibrosis during pre-clinical development could improve the drug discovery process and provide potential savings in drug development. Speaking generally, the use of better biomarkers in pre-clinical development could reduce the average drug development costs by >$100 million.

BRIEF SUMMARY OF THE INVENTION

Disclosed herein are methods and articles for determining the progression or regression of liver fibrosis in a mammalian subject. In some embodiments, the methods comprise detecting differential expression of at least twenty-five genes listed in Table 4 and selected from the list below, or an ortholog thereof corresponding to the mammalian subject. In particular, the methods comprise detecting differential expression of at least twenty-five genes selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof corresponding to the mammalian subject, in a biological sample from the subject. In some embodiments, the methods comprise detecting differential expression of at least 30, at least 35, at least 40, at least 45, or at least 50 genes set forth in Table 4, or corresponding mammalian orthologs thereof.

In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 proteins, peptides and/or amino acids which is encoded by a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In yet another embodiment the proteins, peptides and/or amino acids can be detected in plasma or serum.

In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 gene regulators which correspond to the gene set forth in Table 4, or corresponding mammalian orthologs thereof. In yet another embodiment the gene regulators can be detected in plasma or serum.

In some embodiments, the subject is a rat, mouse, guinea pig, pig, rabbit, dog, cat, cow, horse, or human. In some embodiments, the subject is a human.

Also disclosed are methods for detecting early stage liver disease in a mammalian subject, comprising assaying a biological sample from the subject for differential expression of at least 25 genes selected from Table 4 and selected from the list above and corresponding mammalian orthologs thereof wherein the differential expression of the at least 25 genes is indicative of early stage liver disease in the subject. In some embodiments, the method involves assaying the biological sample for differential expression of at least at least 30, at least 35, at least 40, at least 45, or at least 50 of the genes set forth in Table 4. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 proteins, peptides and/or amino acids which is encoded by a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 regulators which correspond to a gene set forth in Table 4, or corresponding mammalian orthologs thereof.

In some embodiments, differential expression of each of the at least 25 genes by an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least 25 genes by an amount of at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is indicative of early stage liver disease.

In some embodiments, differential expression of each of at least 25 proteins, peptides and/or amino acids by an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least 25 proteins, peptides and/or amino acids by an amount of at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is indicative of early stage liver disease.

In some embodiments, differential expression of each of at least 25 gene regulators by an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least 25 gene regulators by an amount of at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is indicative of early stage liver disease.

In some embodiments, increased expression of at least one gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ce12; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one protein, peptide or amino acid which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ce12; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ce12; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Cc/2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb, Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one protein, peptide or amino acids which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Cc/2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb, Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Cc/2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb, Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one protein, peptide or amino acids which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and mammalian orthologs thereof.

In some embodiments, decreased expression of at least one gene selected from the following group is indicative of early stage liver disease: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.

In some embodiments, decreased expression of at least one protein, peptide or amino acid which is encoded by a gene selected from the following group is indicative of early stage liver disease: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.

In some embodiments, decreased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.

In some embodiments, the methods disclosed herein detect early stage liver disease with at a sensitivity of at least 70%, 75%, 80%, 85%, 90%, or at least 95% sensitivity. In some embodiments, the methods disclosed herein detect early stage liver disease with at least 70%, 75%, 80%, 85%, 90%, or at least 95% specificity.

In accordance with any of the embodiments described herein, the biological sample may be selected from blood, plasma, serum, urine, or a liver biopsy.

In accordance with any of the embodiments described herein, differential expression may be determined by quantification of the levels of the proteins encoded by the genes, such as by Western blotting, ELISA or mass spectrometry. Additionally or alternatively, differential expression may be determined by quantification of corresponding mRNA, cDNA or miRNA levels, such as by using an oligonucleotide array comprising probes specific to mRNA, cDNA or miRNA corresponding to each of the twenty-five genes.

In accordance with other embodiments, there are disclosed methods of identifying whether a compound increases or decreases the differential expression of at least one gene selected from the following list, comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Co14a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhi, Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMa; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof, contacting the cell with a test compound; and determining whether the differential expression of the at least one gene is increased or decreased in the presence of the test compound.

In accordance with other embodiments, there are disclosed methods of identifying whether a compound increases or decreases the differential expression of at least one protein, peptide or amino acid which is encoded by a gene selected from the following list, comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Co14a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhi, Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMa; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof, contacting the cell with a test compound; and determining whether the differential expression of the at least one gene is increased or decreased in the presence of the test compound.

In accordance with other embodiments, there are disclosed methods of identifying whether a compound increases or decreases the differential expression of at least one gene regulator which corresponds to a gene selected from the following list, comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Co14a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhi, Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMa; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof, contacting the cell with a test compound; and determining whether the differential expression of the at least one gene is increased or decreased in the presence of the test compound.

In accordance with other embodiments, there are disclosed methods of treating liver disease, comprising administering to a mammalian subject in need thereof, a therapeutically effective amount of a compound identified by the disclosed methods to decrease expression of a gene selected from the group consisting of Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagin2: RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof and/or to differentially express a gene selected from the group consisting of Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof.

In accordance with other embodiments, there are disclosed methods of treating liver disease, comprising administering to a mammalian subject in need thereof, a therapeutically effective amount of a compound identified by the disclosed methods to decrease expression of a protein, peptide or amino acid which is encoded by a gene selected from the group consisting of Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagin2: RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof and/or to differentially express a gene selected from the group consisting of Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof.

In accordance with other embodiments, there are disclosed methods of treating liver disease, comprising administering to a mammalian subject in need thereof, a therapeutically effective amount of a compound identified by the disclosed methods to decrease expression of a gene regulator which corresponds to a gene selected from the group consisting of Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagin2: RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; S/c25a24, and mammalian orthologs thereof and/or to differentially express a gene selected from the group consisting of Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Sod2; Taln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Igfbp3; Igfals; Lamc2; Lgals1; Lgals3 bp; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and mammalian orthologs thereof.

In accordance with other embodiments, there are disclosed arrays comprising at least twenty-five target oligonucleotides immobilized on a substrate, wherein the target oligonucleotide each comprise a sequence that is specifically hybridizable to mRNA, cDNA or miRNA corresponding to one of the at least twenty-five genes from Table 4, and mammalian orthologs thereof, such that the array comprises at least one target oligonucleotide specifically hybridizable to each of the at least twenty-five genes. In some embodiments, the target oligonucleotides are labelled with a detectable label. In some embodiments, the target oligonucleotides comprise cDNA-specific sequences, wherein the cDNA-specific sequences comprises at least one nucleotide that differs from the corresponding genomic DNA. In some embodiments, there is provided an apparatus comprising an array as disclosed herein.

In accordance with other embodiments, there are disclosed kits for the diagnosis of liver disease, comprising at least twenty-five detectably labelled oligonucleotides, wherein the oligonucleotides comprise a sequence that is specifically hybridizable to mRNA, cDNA or miRNA corresponding to at least twenty-five separate genes from Table 4, and mammalian orthologs thereof, such that the kit comprises at least one detectably labelled oligonucleotide specifically hybridizable to each of the at least twenty-five genes.

In accordance with other embodiments, there are disclosed kits for the diagnosis of liver disease, comprising at least twenty-five antibodies, or antigen binding fragments thereof, each capable of binding to one of at least twenty-five separate proteins encoded by genes from Table 4, and mammalian orthologs thereof, such that the kit comprises at least one antibody or fragment thereof that specifically binds to each of the proteins encoded by each of the at least twenty-five genes.

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

FIGS. 1A-1F exemplify dose-dependent liver pathology and pre-fibrotic gene expression after 4,4′-methylenedianiline. Livers from rats administered 0, 8.1, 22, 59.7, and 162 mg/kg 4,4′-methylenedianiline per day for five days (n=4 per group) were stained with hematoxylin and eosin and scored for histopathological evidence of bile duct hyperplasia and fibrosis.

FIGS. 1A and 1B are representative images from a control liver (FIG. 1A) and the liver of a 4,4′-methylenedianiline-treated rat (FIG. 1B) at 10× magnification. FIG. 1C depicts the combined results for histopathological scores as percent of animals with pathology showing a dose-dependent increase in severe pathology. FIG. 1D exemplifies a decrease in body weight gain over the five experimental dosing days. FIGS. 1E and 1F depict dose-dependent increases in gene expression for the pre-fibrosis indicators Tgfb1 (FIG. 1E) and Timp1 (FIG. 1F) by qPCR. NS, not significant; *, p<0.05 by one sample t-test comparing to a theoretical mean of 1.0; black arrow, bile duct hyperplasia. Scale bar denotes 100 μm.

FIGS. 2A-2F exemplify dose-dependent liver pathology and pre-fibrotic gene expression in rats after exposure to allyl alcohol. Livers from rats administered 0, 4.5, 9.7, 20.9, and 45 mg/kg allyl alcohol per day for five days (n=4 per group) were stained with hematoxylin and eosin and scored for histopathological evidence of bile duct hyperplasia and fibrosis.

FIGS. 2A and 2B are representative images from a control liver (FIG. 2A) and a liver from an allyl alcohol-treated rat (FIG. 2B; 45 mg/kg) at 10× magnification. FIG. 2C depicts combined results for histopathological scores as percent of animals with pathology showing a dose-dependent increase in severe pathology. FIG. 2D exemplifies an increase in body weight gain over the five experimental dosing days. FIGS. 2E and 2F depict changes in gene expression for the pre-fibrosis indicators Tgfb1 (FIG. 2E) and Timp1 (FIG. 2F) by qPCR. NS, not significant; *, p<0.05 by one sample t-test comparing to a theoretical mean of 1.0; black arrow, bile duct hyperplasia. Scale bar denotes 100 μm.

FIGS. 3A-3F exemplify dose-dependent vacuolation consistent with lipid accumulation without change in prefibrotic gene expression after carbon tetrachloride exposure. Livers from rats administered 0, 200, 360.9, 651.2, and 1175 mg/kg carbon tetrachloride per day for five days (n=4 per group) were stained with hematoxylin and eosin or Oil Red 0 and scored for histopathological evidence of vacuolation.

FIGS. 3A and 3B are representative images from a control liver (FIG. 3A) and the liver of a carbon tetrachloride-treated rat (FIG. 3B; 200 mg/kg) at 40× magnification after hematoxylyn and eosin staining; scale bar, 20 μm. FIG.3C is a representative image from carbon tetrachloride-dosed animal after Oil Red 0 staining for lipid accumulation, 20× magnification; scale bar, 50 μm. FIG. 3D exemplifies combined results for histopathological scores as percent of animals with pathology showing a dose-dependent increase in severe pathology. FIG. 3E exemplifies a decrease in body weight gain over the five experimental dosing days. FIG. 3F exemplifies a change in gene expression were insignificant for the pre-fibrosis indicator Tgfb1 by qPCR. NS, not significant by one-sample t-test to a theoretical value of 1.0.

FIGS. 4A-4F exemplify dose-dependent liver pathology consistent with glycogen accumulation and lower expression of pre-fibrotic Tgfb1 gene expression after dexamethasone exposure. Livers from rats administered 0, 1, 6.7, 44.8, or 300 mg/kg dexamethasone per day for five days (n=4 per group) were stained with hematoxylin and eosin and scored for histopathological evidence of cytoplasmic alteration consistent with glycogen accumulation.

FIGS. 4A and B are representative images from a control liver (FIG. 4A) and the liver of a dexamethasone-treated rat (FIG. 4B; 300 mg/kg) at 40× magnification. FIG. 4C depicts the combined results for histopathological scores as percent of animals with pathology showing a dose-dependent increase in severe pathology. FIG. 4D exemplifies decrease in body weight gain over the five experimental dosing days. FIGS. 4E and 4F depict decreased gene expression for the fibrosis indicator Tgfb1 (FIG. 4E) and the lipid accumulation indicator Timp1 (FIG. 4F) by qPCR. NS, not significant; *, p<0.05 by one sample t-test comparing to a theoretical mean of 1.0. Scale bar denotes 20 μm.

FIGS. 5A-5F exemplify dose-dependent NASH liver pathology without change in prefibrotic gene expression in rats after bromobenzene exposure. Livers from rats administered 0, 3.1, 19.8, 124.6, 785 mg/kg bromobenzene per day for five days (n=4 per group) were stained with hematoxylin and eosin and scored for histopathological evidence of vacuolation.

FIGS. 5A and 5B are representative images from a control liver (FIG. 5A) and bromobenzene (FIG. 5B; 785 mg/kg) at 40× magnification. FIG. 5C depicts the combined results for histopathological scores as percent of animals with pathology showing a dose-dependent increase in severe pathology. FIG. 5D exemplifies a decrease in body weight gain over the five experimental dosing days. FIG. 5E shows a slight, statistically insignificant increase in gene expression for the pre-fibrosis indicator Tgfb1 by qPCR, and FIG. 5F shows a statistically significant increase in the lipid accumulation indicator Timp1 by qPCR. NS, not significant by one sample t-test comparing to a theoretical mean of 1.0.

FIGS. 6A-6D exemplify periportal fibrosis in rats after five-day oral administration of 162 mg/kg/day 4,4′-methylenedianiline and pre-fibrogenic lesions in centrilobular region after 200 mg/kg/day carbon tetrachloride administration.

FIG. 6A exemplifies bile duct in control livers; dark gray denotes normal collagen. FIG. 6B exemplifies periportal region, with increased collagen (fibrosis) and bile duct hyperplasia. 40× magnification. FIG. 6C exemplifies centrilobular vein in control animals. FIG. 6D exemplifies centrilobular collageous accumulation demonstrated by a dark gray halo rimming a centrilobular vein in carbon tetrachloride-treated animals. 40× magnification; black scale bar, 20 μm. Masson's trichrome.

FIG. 7 exemplifies the positive correlation between liver log₂ fold-changes in gene expression in data from DrugMatrix and the disclosed Bioplex data. A comparison of log₂ fold-changes of panel genes using data from Drug Matrix with fold changes obtained with data from our multiplex experiments revealed a positive correlation (R²=0.79). We used log₂ fold-changes in gene panel expression associated with fibrogenic chemicals that show histopathological evidence of periportal or subcapsular fibrosis. Allyl alcohol, 4,4′-methylenedianiline, 1-naphthyl isothiocyanate, crotamiton, testosterone, carvedilol, carmustine, vinblastine, β-estradiol, and bezafibrate (5-7 days oral administration or intraperitoneal injection) at various doses scored fibrosis-positive in the DrugMatrix study. Allyl alcohol and 4,4′-methylenedianiline at high doses scored positive for fibrosis in the present study.

FIG. 8 exemplifies hierarchical biclustering of log₂ fold-changes in gene expression patterns for 67 genes on the fibrosis gene panel in non-prefibrogenic and prefibrogenic pathologies. Log₂ fold-changes were determined for presumptive fibrosis gene indicators by multiplexed spectrophotometric Bioplex assay and visualized by hierarchical biclustering. 4,4′-MDA, 4,4′-methylenedianiline; 0-no observable pathology; 2-mild pathology (>30-60% of tissue affected); 3-moderate pathology (>60-80% of tissue affected). Data were standardized; the right side of the scale bar indicates higher expression relative to mean and the left side of the scale bar indicates lower expression relative to mean. The genes listed are in the same order as Table 1.

FIG. 9 exemplifies differentiable gene signature pattern for fibrogenic compounds with histopathological evidence of fibrosis. Expression (log₂ fold-change over vehicle control) for 67 signature fibrogenic genes were plotted in order of the biclustering analysis (see FIG. 7 and Table 1). Bromobenzene, carbon tetrachloride, and dexamethasone exposures correlated with histopathological evidence of vacuolation and/or glyocgen accumulation [Nonfibrogenic Compounds, (Fibrosis−)]. High-dose 4,4′-methylenedianiline and allyl alcohol exposures were associated with fibrosis histopathology [Fibrogenic Compounds, (Fibrosis+)]. Low-dose 4,4′-methylenedianiline, allyl alcohol, and all doses of carbon tetrachloride were fibrogenic chemicals without fibrosis (Fibrosis−). Dashed lines represent the 1.5-fold threshold for significance.

FIG. 10 exemplifies expression of four genes in a co-expression module containing A2m, an indicator on the FibroSure panel of biomarkers for steatohepatitis and liver fibrosis. Expression of four genes in a co-expression module associated with A2m was plotted in exposure groups segregated by chemical. Bromobenzene, carbon tetrachloride, and dexamethasone exposures correlated with histopathological evidence of vacuolation and/or glycogen accumulation. High-dose 4,4′-methylenedianiline and allyl alcohol exposures were associated with fibrosis histopathology without evidence of vacuolation. MDA, 4,4′-methylenedianiline; AA, allyl alcohol, BB, bromobenzene, CT, carbon tetrachloride; DEX, dexamethasone (doses in mg/kg).

FIG. 11 exemplifies a summary of differentially expressed genes (DEGs) by putative classification in the fibrogenic gene signature panels. “Upregulated” indicates those genes that are expressed more than 1.5 times higher than under control conditions, and “downregulated” indicates those genes that are expressed more than 1.5 times lower than under control conditions, and “no change” indicates those genes that are expressed within 1.5 times higher than and 1.5 times lower than under control conditions from the heat-map in FIG. 8; ECM, extracellular matrix; *, results reported in the literature at later stages in disease progression with overt fibrosis and/or cirrhosis phenotypes.

FIG. 12 exemplifies a differential gene signature pattern for rats treated with fibrogenic compounds with histopathological evidence of fibrosis. Expression (log₂ fold-change over vehicle control) for 67 signature fibrogenic genes were plotted in decreasing level of log₂ fold-change in the fibroplasia positive samples. The genes within the unshaded dashed box on the left represent genes unregulated in the fibroplasia positive sample relative to the controls. The genes within the shaded dashed box represent genes where a non-significant level of differential expression was found relative to the controls. The genes within the shaded dashed box on the right represent genes downregulated in the fibroplasia positive sample relative to the controls.

FIG. 13(A) exemplifies a Venn diagram indicating genes associated with fibrosis, inflammation, and necrosis endpoints (Group 1 experimental animals) unique to fibrosis endpoint, inflammation, or necrosis.

FIG. 13(B) exemplifies 24 genes associated with fibrosis, inflammation, and necrosis endpoints (Group 1 experimental animals) unique to the fibrosis endpoint alone identified by interference analysis (FDR<0.05 for necrosis, fibrosis, inflammation; ANOVA with contrasts). *, potential early indicators of fibrotic injury; genes differentially regulated in early fibrosis

FIG. 14 exemplifies phenotypic anchoring of multiplexed gene, protein, and miRNA biomarker signatures in plasma to adverse outcome pathways of liver fibrosis

DETAILED DESCRIPTION OF THE INVENTION

Disclosed herein are methods and articles (e.g., gene arrays or antibodies) for determining the progression or regression of liver fibrosis, for the diagnosis of liver disease, and for screening compounds for hepatotoxicity and efficacy against liver fibrosis. Related therapeutic methods also are disclosed. The methods and article relate to a panel of at least twenty-five genes whose differential expression is indicative of liver fibrosis, liver disease, and/or hepatotoxicity. In general, changes in gene expression levels precede the changes in tissue-level that can be observed in histopathological analysis or clinical chemistry analysis. The disclosed panel allows for earlier identification of liver fibrosis or liver disease than can be observed in other approaches, as demonstrated by the carbon-tetrachloride exposure study set forth below.

Definitions

Technical and scientific terms used herein have the meanings commonly understood by one of ordinary skill in the art to which the present invention pertains, unless otherwise defined. Reference is made herein to various methodologies known to those of ordinary skill in the art. Publications and other materials setting forth such known methodologies to which reference is made are incorporated herein by reference in their entireties as though set forth in full. Any suitable materials and/or methods known to those of ordinary skill in the art can be utilized in carrying out the present invention. However, specific materials and methods are described. Materials, reagents and the like to which reference are made in the following description and examples are obtainable from commercial sources, unless otherwise noted.

As used herein, the singular forms “a,” “an,” and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.

The term “about” and the use of ranges in general, whether or not qualified by the term about, means that the number comprehended is not limited to the exact number set forth herein, and is intended to refer to ranges substantially within the quoted range while not departing from the scope of the invention. As used herein, “about” will be understood by persons of ordinary skill in the art and will vary to some extent on the context in which it is used. If there are uses of the term which are not clear to persons of ordinary skill in the art given the context in which it is used, “about” will mean up to plus or minus 10% of the particular term.

As used herein “subject” denotes any animal, including humans. The term “mammalian subject,” includes all mammalian animals, such as rat, mouse, guinea pig, pig, rabbit, dog, cat, cow, horse, and human subjects.

As used herein, the phrases “therapeutically effective amount” and “therapeutic level” mean that dosage or plasma concentration in a subject, respectively, that provides the specific pharmacological response for which the physiologically active agent is administered in a subject in need of such treatment. It is emphasized that a therapeutically effective amount or therapeutic level will not always be effective in treating the target conditions/diseases, even though such dosage is deemed to be a therapeutically effective amount by those of skill in the art. For convenience only, exemplary dosages, drug delivery amounts, therapeutically effective amounts and therapeutic levels are provided below with reference to adult human subjects. Those skilled in the art can adjust such amounts in accordance with standard practices as needed to treat a specific subject and/or condition/disease.

As used herein, the term “differential expression” refers to gene expression on the RNA/mRNA level, protein level, or both RNA/mRNA and protein levels as compared to a reference level of gene expression (control), e.g., an increased or decreased gene expression on the RNA/mRNA level, protein level, or both RNA/mRNA and protein levels. In some embodiments, the reference level of gene expression is gene expression from a normal animal or cell, lacking evidence of liver fibrosis. In some embodiments, the reference level of gene expression is gene expression from an animal or cell known to be positive for liver fibrosis. In some embodiments, the liver fibrosis can be that which accompanies either early stage or late stage liver disease.

As used herein, the terms “gene” and “gene encoding a protein” refer to any nucleic acid sequence or portion thereof with a functional role in encoding or transcribing a protein.

As used herein, the terms “mRNA” and “messenger RNA” refer to RNA molecules that convey genetic information from DNA to the ribosome, where they specify the amino acid sequence of the protein products of gene expression.

As used herein, the terms “cDNA” and “complementary DNA” refer to double-stranded DNA synthesized from a messenger RNA (mRNA) template in a reaction catalysed by the enzyme reverse transcriptase.

As used herein, the terms “miRNA” and “micro RNA” refer to a small non-coding RNA molecule found in plants, animals, and some viruses, which functions in RNA silencing and post-transcriptional regulation of gene expression.

As used herein, the term “oligonucleotide” refers to oligonucleotides that bind in a base-specific manner to a complementary strand of nucleic acid. Such oligonucleotides also include peptide nucleic acids, and other nucleic acid analogs and nucleic acid mimetics.

As used herein, the DrugMatrix database refers to a public repository of microarray data, histopathology, and clinical chemistry data from more than 3,200 drug and toxicant exposures in rats. The DrugMatrix database was analyzed to identify gene signatures related to late stage liver disease.

As used herein, “sensitivity” refers to the true positive rate. As used herein, “specificity” refers to the true negative rate.

In some embodiments, the methods and articles disclosed herein are useful for determining the progression or regression of liver fibrosis in a subject, or for assessing the presence and/or stage of progression of fibrotic injury using a liver biopsy specimen or a biological sample from the subject, with greater sensitivity and specificity than current practices (such as 100% sensitivity and 84% specificity). Further, in some embodiments, the disclosed methods can be used with non-invasively obtained biological samples (e.g., blood, serum, urine, etc.) which will aid in fibrosis diagnosis at a fraction of the cost of a liver biopsy.

Specific applications make possible the diagnosis of adverse health effects after toxic chemical injury without the need for identification or characterization of the chemical which caused the injury. Thus, instead of developing an impractical number of exposure-based assays, a single assay can diagnose adverse health effect regardless of the nature of the chemical which caused the injury.

Other specific applications pertain to the diagnosis of liver fibrosis without the need for histopathology. In specific embodiments, the methods are used in drug development, to assess hepatotoxicity of drug candidates without requiring histopathological evaluation, which is labor intensive and requires a board-certified histopathologist to properly diagnose. Current procedures can only diagnose later stages of fibrotic injury. Most molecular biology laboratories are staffed with trained veterinary pathologists with the capability to read and accurately diagnose specimens. The disclosed inventions circumvent the need for a trained, board-certified histopathologist, representing a significant cost savings by allowing researchers earlier, more accurate diagnoses without extensive histopathological training.

Other specific applications pertain to commercial products with diagnostic potential, such as handheld devices and kits for use in clinical and research settings. Integration of kits into standard drug development will aid in earlier identification of compounds with fibrotic potential and produce significant cost savings to the pharmaceutical industry.

Some embodiments of the methods and articles disclosed herein are useful for identifying drugs that may induce hepatotoxicity, and for developing drugs useful against hepatotoxicity.

Further, in some embodiments, the disclosed methods can be used for toxicity screening in a manner than can predict liver fibrosis earlier than other known methods.

Accordingly, disclosed herein are methods and articles for determining the progression or regression of liver fibrosis, or for diagnosing liver disease, in a subject. In some embodiments, the method comprises detecting differential expression of at least twenty-five separate genes listed in Table 4, or the orthologs thereof corresponding to the subject. In some embodiments, the method comprises detecting differential expression of at least twenty-five genes selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof, in a biological sample from the subject. In some embodiments, the methods comprise detecting differential expression of at least 30, at least 35, at least 40, at least 45, or at least 50 genes selected from Table 4. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 proteins, peptides and/or amino acids which is encoded by a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 gene regulators which correspond to a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In yet another embodiment the gene regulators can be detected in plasma or serum.

In some embodiments, the methods are useful for detecting early stage liver disease in a subject, such as by assaying a biological sample from a subject for differential expression of at least twenty-five separate genes selected from Table 4 and orthologs thereof, wherein the differential expression of the at least twenty-five genes is indicative of early stage liver disease in the subject. In some embodiments, the methods involve assaying the biological sample from the subject for differential expression of at least 30, at least 35, at least 40, at least 45, or at least 50 genes selected from Table 4. In some embodiments, the at least twenty-five genes are selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 proteins, peptides and/or amino acids which is encoded by a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In some embodiments, the methods comprise detecting differential expression of at least 25, at least 30, at least 35, at least 40, at least 45, or at least 50 gene regulators which correspond to a gene set forth in Table 4, or corresponding mammalian orthologs thereof. In yet another embodiment the gene regulators can be detected in plasma or serum. In some embodiments, the different expression is increased expression relative to a control.

In some embodiments, differential expression of each of the at least twenty-five genes in an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least twenty-five genes by at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is further indicative of early stage liver disease. In some embodiments, differential expression of each of at least 25 proteins, peptides and/or amino acids by an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least 25 proteins, peptides and/or amino acids by an amount of at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of each of at least 25 gene regulators by an amount of at least 0.5 fold (log₂) as compared to a control is indicative of early stage liver disease. In some embodiments, differential expression of at least one of the at least 25 gene regulators by an amount of at least 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, 2.0, 2.5, or 3 fold (log₂) as compared to a control is indicative of early stage liver disease.

In some embodiments, increased expression at least twenty-five genes selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof, is indicative of early stage liver disease.

In some embodiments, increased expression of at least one protein, peptide or amino acid which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ce12; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-DMd; Capg; Pkm2; Ce12; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24, and mammalian orthologs thereof.

In some embodiments, increased expression of least twenty-five genes are selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2, and orthologs thereof, is indicative of early stage liver disease.

In some embodiments, increased expression of at least one protein, peptide or amino acids which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Cc/2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb, Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Cc/2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb, Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2, and mammalian orthologs thereof.

In some embodiments, increased expression of at least twenty-five genes selected from the group consisting of: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and n orthologs thereof, is indicative of early stage liver disease.

In some embodiments, increased expression of at least one protein, peptide or amino acids which is encoded by a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and mammalian orthologs thereof.

In some embodiments, increased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce, and mammalian orthologs thereof.

In some embodiments, decreased expression of a gene selected from the group consisting of: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof is indicative of early stage liver disease.

In some embodiments, decreased expression of at least one protein, peptide or amino acid which is encoded by a gene selected from the following group is indicative of early stage liver disease: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.

In some embodiments, decreased expression of at least one gene regulator which corresponds to a gene selected from the following group is indicative of early stage liver disease: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.

Expression of any one or more of Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and orthologs thereof, has not heretofore been associated with liver fibrosis or liver disease. Thus, in some embodiments, there are provided methods of detecting the expression of at least one of these genes, or quantifying levels of mRNA, miRNA or cDNA corresponding to at least one of these genes, in a biological sample from a subject.

In some embodiments, the subject is suspected of having, or at risk of developing, liver disease or liver fibrosis. In some embodiments, differential expression of at least one of these gene compared to a control is determined. In some embodiments, increased expression of at least one of Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Sod2; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp1; Igfbp2; Lamac2; Lgals1; Lgals3; Plod2; Pkm; S100a11; S100a6; Serpine1; Vim; and orthologs thereof is detected and, optionally, indicative of liver disease or liver fibrosis.

In some embodiments, decreased expression of at least one of Angptl3; Igfbp3; Igfals; and orthologs thereof is detected, and, optionally, indicative of liver disease or liver fibrosis. In any of these embodiments, detecting expression of the at least one gene comprises contacting nucleic acid from the biological sample with at least one detectably labelled oligonucleotide specifically hybridizable with the gene, or by other methods described below.

In some embodiments, the methods disclosed herein detect early stage liver disease with a sensitivity of at least 70%, 75%, 80%, 85%, 90%, or at least 95% sensitivity. In some embodiments, the methods disclosed herein detect early stage liver disease with at least 70%, 75%, 80%, 85%, 90%, or at least 95% specificity.

In any of the embodiments described herein, the biological sample may be selected from blood, plasma, serum, urine, or a liver biopsy.

Also disclosed are methods of identifying a compound that increases or decreases the expression of at least one gene associated with hepatotoxicity comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2, Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof; contacting the cell with a test compound; and determining whether the expression of the at least one gene is increased or decreased in the presence of the test compound.

Also disclosed are methods of identifying a compound that increases or decreases the expression of at least one protein, peptide or amino acid which is encoded by a gene associated with hepatotoxicity comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2, Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof; contacting the cell with a test compound; and determining whether the expression of the at least one gene is increased or decreased in the presence of the test compound.

Also disclosed are methods of identifying a compound that increases or decreases the expression of at least one gene regulator which corresponds to a gene associated with hepatotoxicity comprising providing a cell expressing at least one gene selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2, Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof; contacting the cell with a test compound; and determining whether the expression of the at least one gene is increased or decreased in the presence of the test compound.

In some of these embodiments, the at least one gene is selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and orthologs thereof, and the method comprises determining whether the expression of the at least one gene is decreased in the presence of the test compound.

In some of these embodiments, the at least one gene is selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and orthologs thereof, and the method comprises determining whether the expression of the at least one protein, peptide or amino acid which is encoded by the gene is decreased in the presence of the test compound.

In some of these embodiments, the at least one gene is selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfbp2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and orthologs thereof, and the method comprises determining whether the expression of the at least one gene regulator which corresponds to the gene is decreased in the presence of the test compound.

In some embodiments, the at least one gene is selected from the group consisting of: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and othologs thereof and the method comprises determining whether the expression of the at least one gene is increased in the presence of the test compound.

In some embodiments, the at least one gene is selected from the group consisting of: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and othologs thereof and the method comprises determining whether the expression of the at least one protein, peptide or amino acid which is the encoded the gene is increased in the presence of the test compound.

In some embodiments, the at least one gene is selected from the group consisting of: Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and othologs thereof and the method comprises determining whether the expression of the at least one gene regulator which corresponds to the gene is increased in the presence of the test compound.

Also disclosed are methods of treating liver disease, comprising administering to a subject in need thereof, a therapeutically effective amount of a compound identified as decreasing the expression of at least one gene selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfb2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and othologs thereof, and/or increasing the expression of at least one gene selected from the group consisting of Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and other orthologs thereof.

Also disclosed are methods of treating liver disease, comprising administering to a subject in need thereof, a therapeutically effective amount of a compound identified as decreasing the expression of at least one protein, peptide or amino acids encoded by a gene selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfb2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and othologs thereof, and/or increasing the expression of at least one protein, peptide or amino acids which corresponds to a gene selected from the group consisting of Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and other orthologs thereof.

Also disclosed are methods of treating liver disease, comprising administering to a subject in need thereof, a therapeutically effective amount of a compound identified as decreasing the expression of at least one gene regulator which corresponds to a gene selected from the group consisting of: Dsc2; Fam102b; Fam105a; Gpnmb; Pcolce; RT1-Da; RT1-DMA; Slc25a24; Tagln2; Arpc1b; Angptl3; Anxa2; Cd53; Cd9; Cp; C1qb; Fxyd5; Igfb2; Igfbp3; Igfals; Lamac2; Lgals1; Lgals3; Lrp1; Plod2; Pkm; S100a11; S100a6; Serpine1; Serping1; Vim, and othologs thereof, and/or increasing the expression of at least one gene regulator which corresponds to a gene selected from the group consisting of Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and other orthologs thereof.

In any of the embodiments described herein, differential expression may be determined by quantification of the levels of the proteins encoded by the genes. In some embodiments, wherein quantification of the levels of the proteins comprises assaying a sample by Western blotting, ELISA or mass spectrometry.

In any of the embodiments described herein, differential expression may be determined by quantification of the levels of mRNA corresponding to the at least twenty-five genes. In some embodiments, quantification of the levels of the mRNA comprises incubating the mRNA, miRNA, or corresponding cDNA thereof, with an oligonucleotide array. In some embodiments, the mRNA, miRNA or corresponding cDNA thereof, is hybridized to the oligonucleotide array by interaction with a capture probe, wherein the hybridization results in a target:capture probe pair. In some embodiments, the target:capture probe pair is labeled with a biotinylated label probe. In some embodiments, streptavidin-conjugated phycoerythrin (SAPE) is bound to the biotinylated label probe.

Further disclosed herein is an array comprising at least twenty-five target oligonucleotides immobilized on a substrate, wherein each target oligonucleotide comprises a sequence that is specifically hybridizable to mRNA, cDNA or miRNA corresponding to one of at least twenty-five separate genes from Table 4, or orthologs thereof, such that the array comprises at least one target oligonucleotide specifically hybridizable to each of at least twenty-five different genes, such as at least twenty-five selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; or orthologs thereof. In some embodiments, the target oligonucleotides are labelled with a detectable label. In some embodiments, the target oligonucleotides comprise cDNA specific sequence, wherein said cDNA specific sequence comprises at least one nucleotide difference from corresponding genomic DNA. In some embodiments, the target oligonucleotides are labelled directly with a detectable label. In some embodiments, the target oligonucleotides are labelled indirectly with a detectable label. In some embodiments, the detectable label comprises biotin. In some embodiments, streptavidin-conjugated phycoerythrin (SAPE) is bound to the biotin. In some embodiments, the target oligonucleotide is immobilized on the substrate due to binding with a capture probe. In some embodiments, the capture probe is directly immobilized on the surface of the substrate. In some embodiments, the capture probe is indirectly immobilized on the surface of the substrate. In some embodiments, the array further comprises a label extender.

Also disclosed are handheld apparatuses comprising an array as disclosed herein.

Also disclosed are kits for the diagnosis of liver disease, comprising at least twenty-five detectably labelled oligonucleotides, wherein each oligonucleotides comprises a sequence that is specifically hybridizable to mRNA, cDNA or miRNA corresponding to one of at least twenty-five separate genes from Table 4, or orthologs thereof, such that the kit comprises at least one detectably labelled oligonucleotide specifically hybridizable to mRNA, cDNA or miRNA corresponding to each of the at least twenty-five genes, such as at least twenty-five selected from Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof.

Also disclosed are kits for the diagnosis of liver disease, comprising at least twenty-five antibodies, or antigen-binding fragments thereof, wherein each antibody or fragment thereof is capable of specifically binding to one of at least twenty-five separate proteins encoded by genes from Table 4, or orthologs thereof, such that the kit comprises at least one antibody or antigen-binding fragment thereof that specifically binds to each of the at least twenty-five separate proteins, such as at least twenty-five selected from proteins encoded by Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Tgfb1; Vtn; Vhl; and orthologs thereof.

Also disclosed are kits for the diagnosis of liver disease, wherein at least twenty-five separate proteins encoded by genes from Table 4, or orthologs thereof, are directly identified from the spectra of a high accuracy instrument.

EXAMPLES Example 1—Differential Expression Analysis—mRNA

mRNA is isolated and purified from lysed tissue biopsy specimens. The target mRNA is incubated with beads conjugated to capture probes (each probe is an oligonucleotides specific for one of the genes in the panel). The target is hybridized to the probe by a capture extender-capture probe interaction. Specific mRNA targets hybridize overnight to the respective beads. The signal is amplified by incubating mRNA-capture probe pairs by affixing an amplifier affixed to a biotinylated label probe. Streptavidin-conjugated phycoerythrin (SAPE) is bound to the biotinylated probe to amplify the signal. The signal is detected and quantified by Bioplex suspension array instrumentation, which measures the SAPE fluorescence signal proportional to the amount of mRNA transcripts captured by the bead.

Example 2—Differential Expression Analysis—Proteins

Blood and urine specimens are interrogated by standard sandwich enzyme-linked immunosorbent assays (ELISAs) to detect circulating and/or urinary levels of proteins. Briefly, a capture antibody specific for the target analyte is conjugated to the lower surface of a 96-well plate. Plasma, urine, or serum specimens are incubated with the capture antibody to bind analytes in the biofluid. Non-specific proteins are washed away, and the signal is amplified by incubating with a biotinylated secondary antibody, followed by a streptavidin-conjugated amplifier. After washing away non-specific analytes, a colorimetric reagent is added, causing a color change directly proportional in intensity to the amount of target analyte in the sample. A spectrophotometer is used to quantify the change absorbance, and the exact quantity is measured by comparing the absorbance to a standard curve of known concentrations of the target analyte.

Example 3—Determination of Gene Panel

A gene panel was determined using two computational approaches: (1) a co-expression modules approach using iterative signature algorithms (ISA) (Tawa G J, AbdulHameed M D, Yu X, et al. Characterization of chemically induced liver injuries using gene co-expression modules. PLoS One 2014; 9(9):e107230) and (2) a pathway and network analysis approach (AbdulHameed M D, Tawa G J, Kumar K, et al. Systems level analysis and identification of pathways and networks associated with liver fibrosis. PLoS One 2014; 9(11):e112193). DrugMatrix liver gene expression data generated using Affymetrix GeneChip Rat Genome 230 2.0 Arrays was used for further analysis. In the co-expression modules approach, genes were grouped into 78 distinct co-expression modules based on similarity of expression patterns across conditions, each condition defined as a particular compound-dose combination. The characteristic of correlated expression inherent in these modules implied that the module genes are associated with a common biochemical process. The resultant gene co-expression modules can be members of multiple modules. This is consistent with the fact that genes are, in general, associated with multiple biochemical pathways. Gene co-expression modules associated with liver fibrosis were identified as those exhibiting an average absolute activation value >1.5 times control when exposed to compound-dose combinations that cause fibrosis 4. Center genes were identified from these modules as those with absolute activation closest to the module average. These center genes were chosen to be part of a multiplex panel.

In the pathway and network analysis approach, liver fibrosis-relevant genes were identified and mapped to pathways and high-confidence human protein-protein interaction (PPI) networks. The standard differential expression and co-expression analysis approach was carried out using rank product and hierarchical clustering, respectively, to identify liver fibrosis-relevant genes (see, e.g., Gentleman R C, Carey VJ, Bates D M, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome biology 2004; 5(10):R80; and Breitling R, Armengaud P, Amtmann A, Herzyk P. Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS letters 2004; 573(1-3):83-92). These genes were mapped to high-confidence human PPI networks (Yu X, Wallqvist A, Reifman J (2012) Inferring high-confidence human protein-protein interactions. BMC Bioinformatics 13: 79). Cytoscape tools such as KeyPathway Miner and Clusterviz were used to extract network modules (Alcaraz N, Friedrich T, Kotzing T, et al. Efficient key pathway mining: combining networks and OMICS data. Integrative biology: quantitative biosciences from nano to macro 2012; 4(7):756-764). Network modules represent closely connected regions of the network and are expected to participate in similar function. A network module with high activation score in drug matrix liver fibrosis conditions was extracted and also enriched with known fibrosis-related genes. Differentially expressed genes in this module were chosen to be part of a multiplex panel.

Example 4—Analysis of Differential Expression

Candidate genes identified by co-expression modules and pathway/network approaches were fabricated into a custom gene panel using a commercial source (the QuantiGene 2.0 Plex assay, Affymetrix, Santa Clara, Calif.). A total of 71 genes plus 3 housekeeping genes were selected. Using 150 ng RNA input, samples were processed following manufacturer's instructions for purified RNA with use of the HandHeld Magnetic Plate Washer. Plates were read immediately following the final wash using the BioPlex 200 instrument (BioRad, Hercules, Calif.). The following parameters were set on the BioPlex instrument: sample size=100 μL; DD Gate=5,000-25,000; Timeout=45 sec; Bead Event/Bead Region=100.

For each sample, the average signal intensity was determined as recommended by the manufacturer. Duplicates were averaged. The average background signal for each gene was subtracted. Assay limit of detection was determined by adding three standard deviations of assay background signals to the average intensity of the background control wells. All intensities lower than the limit of detection for each probe was set to one unit above the probe's limit of detection. Probes with all intensities below the assay limit of detection were removed from the final analysis. The test gene signal was divided by the average intensities of the three normalization genes (Gapdh, Hprt1, Ppib). For each test gene, the fold change was calculated by dividing the normalized value for the treated samples by the normalized value of the vehicle-treated controls. Fold changes were plotted as log₂ fold change. Gene expression data were imported into Partek Genomics Suite 6.0 (Partek, Inc., St. Louis, Mo.). Principal component analysis was used for multivariate interpretation to determine sources of variation across sample groups (Joliffe I T, Morgan B J. Principal component analysis and exploratory factor analysis. Statistical methods in medical research 1992; 1(1):69-95). Differentially expressed genes were determined by analysis of variance (ANOVA) with contrasts, setting the ANOVA factors as toxicant and the histopathological endpoint of fibrosis (any score >0). ANOVA variables were fibrosis score 0 (none) vs. score of >0 (minimal, mild, moderate, and marked). For hierarchical biclustering, differentially expressed genes were standardized by setting the genes expressed to a mean of zero and scaling to a standard deviation of one. Euclidean geometry was used to cluster row and column dissimilarity using a method of average linkage.

Receiver operator curves were generated to determine the sensitivity and specificity of the gene expression assay compared to standard histological approaches.

Example 5—Testing of Gene Panel Fidelity

To demonstrate the fidelity of the gene panels in comparison to the current gold standards in clinical diagnosis (i.e., histopathology from a tissue section or biopsy specimen), a 5-chemical oral exposure study was conducted in rodents and directly compared both methods were directly compared. The following test chemicals were purchased from Sigma Aldrich Corporation (St. Louis, Mo.): 4,4′-methylenedianiline (CAS No. 101-77-9), dexamethasone (CAS No. 50-02-2), allyl alcohol (CAS No. 107-18-6), bromobenzene (CAS No. 108-86-1), and carbon tetrachloride (CAS No. 56-23-5). All chemical compounds were diluted in corn oil (CAS No. 8001-30-7) (MP Biomedicals, LLC (Solon, Ohio)). The dose volume was 5 mL/kg. Doses were selected based on doses published in the DrugMatrix database, the National Toxicology Program reports, and ATSDR reports.

In vivo rat experiments were performed at Integrated Laboratory Systems (ILS, Research Triangle Park, NC). ILS's Institutional Animal Care and Use Committee approved all experimental procedures. Research was conducted in compliance with the Animal Welfare Act, and other Federal statutes and regulations relating to animals and experiments involving animals and adheres to principles stated in the “Guide for Care and Use of Laboratory Animals” as prepared by the Committee on Care and Use of Laboratory Animals of the Institute of Laboratory Animal Resources, National Research Council in facilities that are fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care, International. Male Sprague-Dawley rats (CD IGS [CRL:CD (SD)]) were purchased from Charles River Laboratories (Stone Ridge, N.Y.). Rats weighing 215-245 g (8 weeks old) were used. Briefly, rats were housed two per cage with a rat tunnel enrichment device (Bio-Serve, Frenchtown, N.J.). Rats were fed a Purina Rodent Diet No. 5002 (Ralston Purina Co., St. Louis, Mo.), supplied ad libitum. Animals received reverse osmosis-treated tap water (City of Durham, N.C.) ad libitum, which was changed at least once weekly. Controls in the animal rooms were set to maintain temperatures between 20-In vivo rat experiments were performed at Integrated Laboratory Systems (ILS, Research Triangle Park, NC). ILS's Institutional Animal Care and Use Committee approved all experimental procedures. Research was conducted in compliance with the Animal Welfare Act, and other Federal statutes and regulations relating to animals and experiments involving animals and adheres to principles stated in the “Guide for Care and Use of Laboratory Animals” as prepared by the Committee on Care and Use of Laboratory Animals of the Institute of Laboratory Animal Resources, National Research Council in facilities that are fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care, International. Male Sprague-Dawley rats (CD IGS [CRL:CD (SD)]) were purchased from Charles River Laboratories (Stone Ridge, N.Y.). Rats weighing 215-245 g (8 weeks old) were used. Briefly, rats were housed two per cage with a rat tunnel enrichment device (Bio-Serve, Frenchtown, N.J.). Rats were fed a Purina Rodent Diet No. 5002 (Ralston Purina Co., St. Louis, Mo.), supplied ad libitum. Animals received reverse osmosis-treated tap water (City of Durham, N.C.) ad libitum, which was changed at least once weekly. Controls in the animal rooms were set to maintain temperatures between 20-25° C. with a relative humidity of 30-70% and a 12-hour light/12-hour dark cycle, lights on at 6:00 AM. Clinically healthy animals were assigned to dose groups using a procedure that stratifies animals across groups by body weight such that mean body weight of each group was not statistically different from any other group using analysis of variance (Statistical Analysis System version 9.2, SAS Institute, Cary, N.C.). Animals were dosed by oral gavage for five consecutive days (+10 minutes from the previous day's dose administration time). Volume was based upon daily body weight.

Animals were observed cageside one hour following daily dose administration, then 1-2 times per day during dosing regimens. Body weights were measured daily prior to dose administration, and prior to euthanasia. Twenty-four hours after the final dose administration, animals were anesthetized with isoflurane then euthanized by exsanguination followed by decapitation. Livers were harvested at necropsy and weighed to within 0.1 g. One half of the left lobe of the liver was fixed in 10% formalin. The remaining half of the left lobe of the liver was flash frozen in liquid nitrogen, then stored below −70° C. Liver specimens were frozen in less than three minutes from time of death.

Formalin-fixed liver specimens were embedded in paraffin blocks. A 5 μm section of liver from each animal was stained with hematoxylin and eosin, Oil Red 0, or Masson's trichrome for microscopic evaluation. The tissues were evaluated by a Board-Certified veterinarian-pathologist (MHB). Tissues were qualitatively scored for degree of pathology on a descriptive scale with the following distribution: None, 0% of tissue affected; Minimal, >0-30% of tissue affected; Mild, >30-60% of the tissue affected; Moderate, 60-80% of the tissue affected; Marked, >80% of the tissue affected.

Working on dry ice, a portion (−10 mg) of flash-frozen liver was cut from each sample and transferred to a clean, labeled tube. Total RNA was then isolated using Qiagen's miRNeasy 96 kit (Qiagen, Valencia, Calif.) following manufacturer's instructions with a final elution volume of −150 μL (2×75 μL). The quality and quantity of RNA samples were evaluated with a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, Calif.), using the Agilent RNA 6000 Nano Reagents and a multiwell NanoDrop 8000 spectrophotometer (Thermo Fisher Scientific, Waltham, Mass.).

Using 1 μg RNA input, cDNA was generated using a QuantiTect Reverse Transcription kit (Qiagen, Valencia, Calif.) following manufacturer's instructions. Applied Biosystems SYBR Green Master Mix was used in a 20 μL qPCR reaction with 2 μL of cDNA template and a 2.tM final concentration of each primer. A total of five genes were targeted (Gapdh, Actb, Timp1, Tgfbl, and Psma5), two of which served as the endogenous controls (Gapdh and Actb). An Applied Biosystems 7500 Real-Time PCR System (Applied Biosystems, Foster City, Calif.) was used for thermal cycling and fluorescence detection using the default settings for Quantitation-Comparative CT with SYBR® . . . Green Reagents which uses the following scheme: 95° C. for 10 minutes followed by 40 cycles of: 95° C. for 15 seconds, 60° C. for 1 minute, and a fluorescence signal read. Al! primers were obtained from Integrated DNA Technology's PrimeTime qPCR primer library (Integrated DNA Technologies, Coralville, Iowa).

Data was imported into GraphPad Prism (GraphPad Software, Inc.; LaJolla, Calif.) for analysis. A nonparametric Kruskal-Wallis analysis of variance by ranks with post hoc Dunnett's multiple comparison test was used to determine statistical difference among dose groups. A one sample t-test compared to a theoretical mean of 1.0 fold change was used to determine difference from control for each dose group. A p-value<0.05 was used as a cutoff for statistical significance.

Histopathology

Male Sprague-Dawley rats were administered toxicants by oral gavage for five days (see Table 1). At high doses, the fibrogenic chemicals 4,4′-methylenedianiline (FIGS. 1A and 1B) and allyl alcohol (FIGS. 2A and 2B) caused bile duct hyperplasia comorbid with fibrosis and necrosis. Both chemicals caused a dose-dependent increase in the degree of fibrosis, although the fibrosis phenotype showed more heterogeneity among the animals dosed with allyl alcohol than 4,4-methylenedianiline (FIGS. 1C and 2C). Animals receiving the highest doses gained less weight over the five-day exposure interval than their low-dose counterparts (FIGS. 1D and 2D). Gene expression of the fibrosis-related genes Tgfbl and Timp1 showed a dose-dependent increase as measured by qPCR (FIGS. 1E, 1F, 2E, and 2F).

TABLE 1 Chemical compound-dose groups and presumptive mechanisms of toxicity after oral exposure in rats Dose (mg/kg) Mechanism of Predicted Chemical Structure (n = 4 rats/dose gorup) Hepatotoxicity Histopathology Allyl Alcohol

0, 4.5, 9.7, 20.9, 45 Free radical damage by toxic metabolite Fibrosis, bile duct hyperplasia (acrolein):

Bromobenzene

0, 3.1, 19.8, 124.6, 785 Free radical damage by toxic metabolite:  

Fatty liver, necrosis Carbon tetrachloride CCl₄ 0, 200, 360.9, 651.2 Free radical damage by Fatty liver, necrosis, toxic metabolite, lipid fibrosis (delayed-onset) peroxidation •CCl₃ Dexamethasone

0, 1, 6.7, 44.8, 300 Indirect lipid accumulation by increased circulating triglycerides Minimal; glycogen accumulation 4,4′-Methylenedianiline (MDA)

0, 8.1, 22, 59.7, 162 Conversion to toxic metabolite by n-acetyl- transferase enzymes Fibrosis, necrosis, bile duct hyperplasia

Carbon tetrachloride caused a dose-dependent increase in vacuolation indicative of lipid accumulation without evidence of fibrosis (FIGS. 3A-3D). Body weight gain was less than controls at all doses (FIG. 3E). The fibrosis-dependent gene Tgfbl was not significantly upregulated at any dose (FIG. 3F).

All doses of dexamethasone resulted in lipemia (milky white plasma) and marked cytoplasmic alteration characteristic of glycogen accumulation (FIGS. 4A-4C), although a definitive confirmation could not be made without periodic acid Schiff s stain. The highest dose caused moderate tissue necrosis affecting >60-80% of the tissue in two animals, resulting in a concomitant decrease in percentage of tissue which could be scored for cytoplasmic alteration (FIG. 4C, 300 mg/kg dose). Body weight loss occurred at all doses (FIG. 4D). Tgfbl was significantly downregulated in animals receiving 1, 6.7, or 300 mg/kg dexamethasone (FIG. 4E). Dexamethasone administration at 44.8 mg/kg caused a similar trend, but the difference was not statistically significant (FIG. 4E). Timp1 expression was more variable among individual animals, but none of the changes were statistically significant (FIG. 4F).

The non-fibrogenic toxicant bromobenzene did not cause histopathological evidence of bile duct hyperplasia or fibrosis at any dose (FIGS. 5A and 5B), but the highest dose caused varying degrees of vacuolation in all experimental animals (FIG. 5C). The observed pathology is consistent with bromobenzene's toxicological classification as a potent inducer of hepatic steatosis. The highest dose of bromobenzene resulted in body weight loss over the study interval (FIG. 5D). Tgfbl and Timp1 expression were not significantly affected at any dose (FIGS. 5E and 5F; p>0.05). However, expression of Psma5, a gene associated with periportal lipid accumulation, was increased in the high-dose group with observable vacuolation pathology (2.2±0.8-fold vehicle control; p<0.05).

Perioportal fibrosis was confirmed by Masson's trichrome staining after 4,4′-methylenediani line administration (162 mg/kg/day) (FIGS. 6A and 6B). Carbon tetrachloride (200 mg/kg/day) caused prefibrotic centrilobular collagenous accumulation (FIGS. 6C and 6D).

Multiplexed Fibrosis Gene Panel

Chemical-dose groups were down-selected based on histopathology to conform to the 96-well assay format of the multiplexed panel of presumptive fibrosis genes. Three of the four dose groups were evaluated for the fibrogenic chemicals allyl alcohol and 4,4′-methylenedianiline. A single dose was selected with group-matched vehicle controls for each of the remaining chemicals. The lowest doses of both carbon tetrachloride and dexamethasone were selected because all doses produced comparable histopathology in both cases. The highest dose of bromobenzene was selected because the vacuolation pathology was only observed at this dose.

Isolated liver RNA was incubated with microbead-bound capture probes specific for the 71 presumptive fibrogenic genes and three housekeeping normalization genes. All fluorescence intensity values for four genes (Dram1, Myoc, Pdgf, and Lama5) fell below the limits of assay detection. These genes were excluded from further analysis. For a complete list of differentially expressed genes, please refer to Table 2.

TABLE 2 Differential Expression of Genes in Rats After Exposure to Toxicants Animal Number 89 90 91 92 9 10 Toxicant 4,4′- 4,4′- 4,4′- 4,4′- Allyl Allyl MDA MDA MDA MDA Alcohol Alcohol Dose (mg/kg) 22 22 22 22 9.7 9.7 Inflammation 0 0 0 0 0 0 Vacuolation 0 0 0 0 0 0 Bile Duct Hyperplasia 0 0 0 0 0 0 and Fibroplasia Cytoplasmic Alteration 2 1 3 1 1 1 Necrosis 0 0 0 0 0 0 Gapdh 2112 2068 1825.5 1732.5 1566.3 1899 Hprt1 577.5 739.8 496.5 405.5 431.3 482.5 Ppib 1429.5 1416.3 1158 1094.3 1091.5 1442.5 A2m −2.855 −0.021 −2.439 −1.215 −0.770 0.285 Cxcl1 −0.229 −0.253 0.128 0.197 0.698 1.963 RT1-DMa −0.243 −0.620 −0.341 0.126 −0.785 −0.228 Arf6 −0.068 −0.041 −0.364 0.202 −0.534 −0.308 Dsc2 0.089 −0.493 −0.175 0.540 −0.340 −0.708 Sod2 −0.025 −0.010 −0.185 0.179 −0.155 −0.147 Cxcl16 −0.760 −2.494 −1.507 0.503 −4.079 −0.608 Lame2 −0.986 −1.330 −1.051 1.090 −4.514 −0.668 Ccl2 −0.478 −2.306 −1.102 0.769 −4.934 −1.072 Col5a2 −0.430 −2.096 −0.679 0.566 −6.430 −0.644 Arrb1 −0.607 −1.924 −1.789 0.833 −5.190 −0.975 Vhl −0.894 −1.708 −1.342 0.643 −5.780 −0.518 Ctgf −0.987 −1.256 −2.405 0.339 −1.559 −0.144 Len2 −0.695 −0.526 −0.938 −0.318 −4.722 −0.302 Lbp −0.004 −0.228 −0.249 0.126 0.122 0.174 S100A11 0.125 −0.544 −0.369 0.746 −1.913 −0.593 Pkm2 0.151 −0.187 −0.404 0.171 −0.384 −0.109 TagIn2 0.349 −0.487 −0.149 0.259 −0.358 −0.197 Cyba 0.311 −0.537 −0.253 0.192 −0.552 −0.259 Capg −0.223 −0.640 −0.784 0.094 −0.909 −0.679 C1qb 0.133 −0.701 −0.250 0.301 0.144 −0.221 Plau −0.214 −0.629 −0.813 0.201 −1.777 −1.011 Fstl1 0.242 −0.419 0.004 0.448 −0.414 −0.240 Vim 0.268 −0.815 −0.412 0.554 0.068 −0.253 Col4a1 −0.158 −0.477 −0.335 0.500 −0.348 −0.006 Fbn1 −0.228 −0.665 −0.692 0.339 −0.675 −0.004 Nid1 0.048 −0.571 −0.071 0.340 −0.885 −0.486 Col1a1 −0.465 −2.285 −1.409 0.321 −0.671 −0.901 Lgals1 0.667 −1.034 −0.065 0.713 −1.446 −1.536 Arpc1b −0.510 −1.326 −1.129 0.324 −4.326 −0.855 CD53 −0.379 −1.429 −1.351 −0.278 −0.554 −0.680 Itgb2 −0.044 −0.559 −0.772 0.441 −1.022 −0.073 Itga1 −0.084 −0.862 −0.531 −0.224 −0.128 −0.334 RT1-Da 0.436 −0.623 −0.441 −0.237 −0.530 −0.349 Lgals3bp −0.334 −1.112 −0.592 0.101 −1.460 −0.288 Pcolce −0.165 −0.858 −0.115 0.247 −1.394 −0.468 CP 0.011 0.004 −0.198 0.329 0.011 0.156 Igfbp2 −0.276 −0.608 −1.094 0.428 −4.542 0.141 CD9 −0.052 −0.660 −0.131 0.455 −2.005 0.118 Serpine1 −0.318 −0.576 −0.297 0.540 −3.045 −0.265 Lox −0.021 0.268 −0.131 0.718 −3.732 −0.312 Plod2 −0.334 −0.460 −0.434 0.789 −3.558 −0.059 Plat 0.246 −0.329 −0.433 0.878 −3.393 −0.378 Slc25a24 −0.090 −0.239 0.153 0.682 −3.758 −0.208 Fam102b −0.168 −0.683 −0.353 0.253 −3.759 −0.607 Col1a2 −0.675 −1.296 −0.898 0.391 −4.077 −0.239 Fxyd5 −0.040 −0.415 −0.228 0.500 −2.713 0.100 Fam105a −0.331 −0.801 −0.384 0.473 −2.213 −0.816 Timp1 0.232 −0.937 −0.283 0.424 −4.028 −1.429 S100A6 −0.139 −0.974 −0.468 0.537 −1.038 −0.283 Lgals3 0.120 −0.871 −0.263 0.423 −0.193 −0.673 Gpnmb −0.185 −1.170 −1.038 −0.108 −1.018 −0.944 Anxa2 0.641 −0.897 −0.674 0.911 −2.047 −0.783 Lum −1.405 −0.867 −1.587 0.340 −0.529 −1.211 Mmp2 −0.393 −0.668 −0.568 0.049 −0.238 −0.147 Igfbp1 −1.313 −0.371 −0.485 1.098 −0.901 0.209 Cyp2c11 −0.399 −0.060 0.353 −0.018 0.297 0.524 Angptl3 −0.284 −0.570 −0.082 0.202 −0.018 0.212 Apoc −0.107 −0.053 −0.016 0.120 0.502 0.059 Vtn −0.090 −0.056 0.010 0.229 0.290 0.216 Tgfb1 −0.117 −0.343 −0.283 0.105 −0.040 0.073 Igfbp3 −0.436 −0.102 −0.746 0.167 −0.267 −0.489 Cxcl12 −0.092 −0.288 0.201 0.478 −0.268 −0.666 Igfals −0.182 −0.197 −0.087 0.156 0.094 −0.511 Serping1 −0.336 −0.214 0.339 0.319 −0.200 −0.502 Fn1 −0.437 −0.481 −0.339 0.548 −0.074 −0.267 Lrp1 −0.604 −0.180 −0.192 0.366 −0.150 0.136 Animal Number 11 12 13 14 15 16 Toxicant Allyl Allyl Allyl Allyl Allyl Allyl Alcohol Alcohol Alcohol Alcohol Alcohol Alcohol Dose (mg/kg) 9.7 9.7 20.9 20.9 20.9 20.9 Inflammation 0 0 0 0 2 3 Vacuolation 0 0 0 0 0 0 Bile Duct Hyperplasia 0 0 0 0 2 3 and Fibroplasia Cytoplasmic Alteration 1 1 1 2 3 2 Necrosis 0 0 0 0 2 3 Gapdh 2050.3 1558 1911.5 2293 2276 1773.8 Hprt1 455 501.3 593.8 565 581 463.5 Ppib 1395.5 1320.5 1609 1773.5 1742.5 1158 A2m −0.080 −0.772 0.452 −0.406 2.458 0.711 Cxcl1 0.048 0.812 0.826 0.452 3.867 0.282 RT1-DMa −0.025 0.294 0.011 −0.537 1.420 0.385 Arf6 −0.150 −0.051 −0.119 −0.124 −0.060 0.108 Dsc2 −0.364 −0.085 0.025 0.042 0.670 −0.244 Sod2 −0.049 −0.003 −0.150 −0.185 0.200 −0.023 Cxcl16 −0.040 −2.546 −0.063 −0.389 0.608 0.071 Lame2 −0.178 −1.023 −0.146 0.242 0.365 0.350 Ccl2 0.278 −1.816 0.305 0.076 0.418 −0.004 Col5a2 −0.269 −0.739 −0.019 −0.137 0.062 −0.045 Arrb1 −0.536 −0.907 0.124 −0.102 0.150 −0.304 Vhl −0.121 −1.756 0.190 0.135 0.177 −0.003 Ctgf −0.814 −3.246 −0.229 −0.151 0.546 0.297 Len2 0.299 −0.168 −1.307 1.010 5.978 −1.214 Lbp 0.547 0.615 0.532 −0.106 2.498 1.177 S100A11 −0.053 −0.021 −0.359 −0.460 0.260 −0.150 Pkm2 −0.206 0.242 0.058 −0.245 0.861 −0.360 TagIn2 −0.024 −0.050 0.310 −0.106 0.495 −0.144 Cyba −0.173 0.122 0.022 −0.226 1.469 −0.265 Capg −0.556 −0.212 −0.107 −0.055 1.543 −0.192 C1qb 0.063 0.323 0.247 −0.106 1.217 0.232 Plau −0.288 0.087 0.010 −0.305 1.013 0.357 Fstl1 −0.177 0.328 0.041 −0.134 −0.516 −0.127 Vim 0.161 0.556 0.029 −0.100 1.145 −0.108 Col4a1 −0.296 0.343 −0.444 0.012 −0.344 0.685 Fbn1 −0.371 0.561 −0.379 −0.744 −0.664 −0.101 Nid1 −0.174 −0.195 0.373 −0.002 −0.328 0.318 Col1a1 −0.415 −0.428 −0.304 −0.538 −0.381 −0.528 Lgals1 0.195 −0.116 0.408 −0.085 0.302 −0.511 Arpc1b −0.301 −0.924 0.248 −0.267 0.827 0.040 CD53 −0.105 −0.427 −0.300 −0.158 1.111 −0.328 Itgb2 −0.136 −0.151 −0.247 −0.103 1.160 0.227 Itga1 0.059 0.355 −0.093 −0.412 1.447 −0.281 RT1-Da 0.099 0.161 −0.167 −0.931 1.985 −0.486 Lgals3bp 0.056 0.102 −0.162 −0.294 0.062 −0.716 Pcolce 0.015 0.196 0.073 0.076 2.330 0.426 CP −0.042 0.291 0.177 0.040 1.368 0.311 Igfbp2 −0.709 −0.193 0.599 −0.195 0.598 −0.446 CD9 −0.059 −0.017 −0.191 −0.428 0.167 0.165 Serpine1 0.011 −0.268 0.380 0.106 0.059 −0.011 Lox −0.046 −0.307 −0.417 −1.068 −0.751 −0.389 Plod2 −0.017 −0.688 −0.114 0.043 −0.133 −0.051 Plat 0.253 0.316 −0.282 0.547 −0.406 −0.391 Slc25a24 −0.024 −0.030 0.255 −0.095 0.475 0.259 Fam102b −0.141 0.241 −0.019 −0.150 0.888 −0.037 Col1a2 −0.128 0.532 −0.168 −0.376 −0.465 0.123 Fxyd5 −0.207 0.189 0.132 0.174 0.732 −0.097 Fam105a −0.534 −0.152 −0.021 −0.045 1.055 −0.053 Timp1 0.325 −0.176 0.366 0.088 0.977 0.347 S100A6 0.360 0.429 0.376 −0.573 0.477 −0.258 Lgals3 −0.691 −0.093 −0.130 −0.298 1.429 −0.491 Gpnmb 0.657 0.046 0.471 −0.359 1.697 0.355 Anxa2 0.042 0.046 0.355 −0.234 0.538 −0.257 Lum −0.995 1.310 1.223 0.281 1.134 −0.094 Mmp2 0.032 0.399 0.286 −0.110 −0.695 0.179 Igfbp1 −0.367 0.547 0.145 −0.001 −0.502 0.821 Cyp2c11 0.168 −0.007 −0.189 −0.144 −1.921 0.345 Angptl3 0.025 0.210 0.028 −0.047 −0.527 0.050 Apoc 0.149 0.028 0.036 −0.195 −0.218 0.314 Vtn 0.102 0.047 −0.095 −0.125 −0.089 0.237 Tgfb1 −0.071 0.315 −0.026 −0.081 −0.570 0.065 Igfbp3 −0.332 0.014 −0.077 −0.824 −1.372 −0.157 Cxcl12 −0.257 0.230 −0.373 −0.298 −0.774 −0.028 Igfals 0.197 −0.459 −0.445 −0.061 −0.832 −0.816 Serping1 −0.133 0.240 −0.232 0.002 0.553 0.220 Fn1 0.210 0.139 −0.134 −0.059 −0.170 0.198 Lrp1 0.187 0.232 0.132 0.020 0.071 0.447 Animal Number 17 18 20 93 94 95 Toxicant Allyl Allyl Allyl 4,4′- 4,4′- 4,4′- Alcohol Alcohol Alcohol MDA MDA MDA Dose (mg/kg) 45 45 45 59.7 59.7 59.7 Inflammation 3 3 2 2 2 3 Vacuolation| 0 0 0 0 0 0 Bile Duct Hyperplasia 3 3 3 2 3 2 and Fibroplasia Cytoplasmic Alteration 3 4 2 4 3 3 Necrosis 3 4 3 1 0 1 Gapdh 2361.3 29950.5 2307.8 2384 3133 2922.5 Hprt1 547.5 896.8 740 1089.8 1052.3 1451 Ppib 1372.8 2253.5 1995.8 1414.8 1548.8 1852 A2m −0.580 4.275 −1.491 −0.640 −0.558 1.003 Cxcl1 0.709 1.478 0.732 0.006 1.807 1.403 RT1-DMa −0.179 1.566 0.265 1.381 2.022 2.522 Arf6 −0.256 0.178 −0.132 0.149 0.370 0.269 Dsc2 −0.171 0.507 0.455 0.258 0.244 0.474 Sod2 −0.161 −0.460 −0.493 −0.094 0.474 0.238 Cxcl16 −1.080 −0.133 −1.040 1.969 1.196 2.174 Lame2 −0.663 −0.451 −0.829 1.485 0.755 1.416 Ccl2 −0.383 0.979 −0.393 1.483 1.928 1.705 Col5a2 −0.380 1.284 −0.148 0.887 0.265 0.427 Arrb1 −0.740 −0.404 −0.991 1.051 0.640 0.525 Vhl −0.599 −0.718 −0.760 0.631 0.018 −0.164 Ctgf 0.129 0.280 −1.205 1.026 0.691 1.013 Len2 0.971 1.169 6.080 4.000 3.904 −1.530 Lbp 0.361 3.078 2.165 2.023 1.422 2.026 S100A11 −0.212 2.960 0.779 2.239 1.096 2.659 Pkm2 0.103 2.906 0.739 1.314 1.491 2.389 TagIn2 −0.062 2.063 0.679 1.404 1.169 1.971 Cyba −0.108 1.351 0.399 1.216 1.165 2.041 Capg −0.205 1.938 0.402 1.169 1.723 2.026 C1qb 0.144 1.031 0.458 0.893 0.937 1.469 Plau −0.162 1.311 0.183 0.941 0.957 1.332 Fstl1 −0.366 0.758 0.206 0.146 −0.373 0.049 Vim 0.242 2.666 0.914 0.931 0.440 1.584 Col4a1 0.229 1.380 0.191 0.698 0.058 0.684 Fbn1 −0.189 1.419 −0.456 0.719 −0.043 0.697 Nid1 −0.377 1.359 0.495 0.747 0.101 0.465 Col1a1 0.086 3.691 0.327 2.154 0.097 2.194 Lgals1 −0.189 3.063 0.892 1.636 0.107 1.896 Arpc1b −0.388 1.059 0.091 1.147 1.069 1.373 CD53 −0.329 0.597 −0.343 0.950 1.045 1.560 Itgb2 −0.060 0.983 0.101 0.709 1.138 1.216 Itga1 −0.051 0.894 0.230 1.064 1.196 1.743 RT1-Da −0.957 −1.800 −0.732 1.431 2.375 2.640 Lgals3bp −0.162 0.589 −0.332 0.425 −0.042 0.829 Pcolce 0.539 3.259 2.844 0.994 0.041 1.107 CP 0.143 0.367 0.647 0.813 0.264 0.806 Igfbp2 −0.600 1.258 0.806 0.776 −0.213 1.037 CD9 −0.024 1.780 0.219 1.728 0.138 1.640 Serpine1 −0.124 2.721 0.135 1.151 1.305 1.475 Lox −0.810 2.071 0.324 0.895 −0.222 1.366 Plod2 −0.544 2.493 0.226 0.920 0.061 1.396 Plat −0.163 2.270 0.392 1.791 0.571 2.379 Slc25a24 −0.100 1.023 0.557 0.681 0.370 0.863 Fam102b −0.248 0.903 0.026 0.577 0.939 0.845 Col1a2 −0.226 2.322 −0.358 0.966 −0.355 0.902 Fxyd5 0.027 2.267 0.487 1.025 0.916 1.613 Fam105a 0.114 1.529 0.324 1.236 1.186 1.900 Timp1 0.025 3.024 1.159 1.871 1.153 2.099 S100A6 0.290 2.362 1.807 0.965 −0.038 1.228 Lgals3 0.123 2.958 1.249 1.931 2.085 2.575 Gpnmb 0.340 3.532 0.925 1.876 1.911 3.162 Anxa2 0.755 2.785 1.558 2.439 1.755 2.514 Lum −0.063 3.392 −0.236 −1.037 −0.339 0.558 Mmp2 −0.333 1.189 −0.434 −0.171 −1.012 −0.273 Igfbp1 0.221 1.272 −0.858 −0.300 −0.689 −0.424 Cyp2c11 0.027 −7.636 −5.217 −4.496 −0.998 −2.003 Angptl3 0.071 −1.620 −0.819 −1.342 −1.123 −1.335 Apoc −0.016 −1.114 −0.462 −0.246 −0.561 −0.801 Vtn 0.017 −1.150 −0.324 −0.546 −0.532 −0.859 Tgfb1 −0.395 −0.983 −0.515 −0.639 −0.667 −0.942 Igfbp3 −0.979 −1.769 −1.970 −2.961 −1.352 −2.494 Cxcl12 −0.990 −1.586 −1.327 −1.347 −1.272 −2.109 Igfals −0.880 −2.148 −0.970 −0.785 −0.893 −1.298 Serping1 −0.218 −0.498 −0.370 −0.220 −0.023 0.055 Fn1 −0.486 −0.195 −0.420 −0.390 −0.812 −0.766 Lrp1 −0.300 −0.419 −0.347 −0.452 −0.348 −0.613 Animal Number 96 97 98 99 100 54 Toxicant 4,4′- 4,4′- 4,4′- 4,4′- 4,4′- Carbon MDA MDA MDA MDA MDA Tetrachloride Dose (mg/kg) 59.7 162 162 162 162 200 Inflammation 2 2 2 2 2 0 Vacuolation 0 0 0 0 0 3 Bile Duct Hyperplasia 2 3 2 3 3 0 and Fibroplasia Cytoplasmic Alteration 1 2 3 2 3 0 Necrosis 1 2 2 2 1 1 Gapdh 2508 2700.5 2891.3 2103.5 2272 2379.5 Hprt1 2073.5 2119.3 2624 1897.8 2070.5 569 Ppib 1909.5 1795.8 2013.5 1461 1412.5 1274.8 A2m −0.515 −0.752 −0.367 0.636 −0.146 −3.423 Cxcl1 1.052 1.645 2.036 2.699 1.178 0.190 RT1-DMa 1.938 1.970 1.713 2.157 1.814 0.225 Arf6 0.145 −0.012 −0.034 0.104 0.197 0.270 Dsc2 0.455 0.394 0.678 0.955 0.720 0.091 Sod2 0.257 0.336 0.432 0.612 0.168 0.022 Cxcl16 2.503 2.029 2.368 2.877 2.768 1.440 Lame2 1.029 0.703 0.793 0.530 1.041 2.323 Ccl2 1.065 1.491 1.899 1.638 2.340 1.671 Col5a2 −0.015 −0.359 0.858 0.442 0.935 1.411 Arrb1 0.108 −0.641 0.602 0.081 0.761 1.846 Vhl −1.077 −1.397 −0.595 −1.062 −0.377 2.369 Ctgf 0.905 1.758 2.136 1.451 1.889 2.135 Len2 3.180 3.402 4.407 4.653 3.803 −1.654 Lbp 2.387 2.111 2.928 2.713 2.458 0.594 S100A11 2.619 2.033 2.948 2.479 3.288 0.119 Pkm2 1.504 1.650 1.865 1.904 2.017 0.077 TagIn2 1.740 1.605 1.734 1.682 2.383 0.218 Cyba 1.810 2.010 1.548 1.991 1.782 0.522 Capg 1.532 1.814 1.658 1.581 1.640 0.433 C1qb 1.301 1.519 1.224 1.246 1.125 0.268 Plau 0.619 1.177 1.067 0.958 1.279 0.039 Fstl1 −0.119 −0.341 0.583 0.306 0.474 −0.259 Vim 1.307 1.272 1.805 1.565 1.565 0.044 Col4a1 0.585 0.211 1.119 1.046 1.114 −0.521 Fbn1 0.605 0.275 1.122 1.128 1.175 −0.149 Nid1 0.461 0.170 0.761 0.787 0.844 −0.021 Col1a1 2.326 1.772 2.933 3.350 2.716 1.336 Lgals1 1.858 1.032 2.647 1.699 2.117 0.936 Arpc1b 1.030 0.946 1.048 0.964 1.356 1.102 CD53 0.774 1.175 0.819 0.838 0.720 0.486 Itgb2 0.694 0.886 0.789 0.754 0.987 −0.115 Itga1 1.001 1.202 0.739 0.951 0.883 0.220 RT1-Da 1.941 2.321 1.129 2.013 1.586 0.559 Lgals3bp 0.713 0.544 0.531 0.265 0.276 0.391 Pcolce 1.109 0.772 1.597 1.301 1.175 0.002 CP 0.697 0.445 0.674 1.008 0.437 −0.227 Igfbp2 0.901 1.443 1.840 1.128 1.008 −0.542 CD9 2.055 1.358 2.688 2.147 2.614 −0.279 Serpine1 2.110 2.887 3.371 2.709 3.163 0.309 Lox 1.400 0.880 2.251 1.957 1.785 −0.215 Plod2 0.943 0.699 1.892 1.531 1.735 −0.129 Plat 2.086 1.548 2.206 1.733 2.853 −0.025 Slc25a24 0.633 0.633 1.136 0.805 1.373 −0.245 Fam102b 0.833 0.111 0.705 0.848 1.119 −0.378 Col1a2 0.998 0.413 1.187 1.817 1.005 0.249 Fxyd5 1.315 1.096 1.541 1.448 1.502 0.160 Fam105a 1.417 1.449 1.702 1.583 1.587 0.309 Timp1 1.999 1.521 2.473 1.865 2.263 0.939 S100A6 1.292 0.849 2.063 1.331 1.619 −0.079 Lgals3 2.499 2.803 2.873 2.782 2.940 0.994 Gpnmb 2.992 3.525 3.032 3.519 2.971 1.494 Anxa2 2.736 2.105 2.876 2.212 2.902 0.553 Lum 0.802 −1.943 0.958 −0.269 1.679 0.298 Mmp2 −0.386 −0.485 −0.564 −0.428 −0.503 −0.062 Igfbp1 0.366 1.713 0.883 −0.527 0.382 0.019 Cyp2c11 −3.316 −4.316 −7.665 −5.415 −6.029 −1.357 Angptl3 −1.715 −1.877 −2.329 −1.959 −2.302 −0.612 Apoc −0.672 −0.874 −1.118 −0.549 −1.212 −0.311 Vtn −0.983 −1.300 −1.045 −0.963 −1.331 −0.291 Tgfb1 −1.056 −1.330 −1.371 −1.473 −1.298 −0.322 Igfbp3 −3.956 −3.946 −3.678 −3.158 −3.073 −0.324 Cxcl12 −2.203 −2.321 −2.314 −2.944 −2.233 0.040 Igfals −1.423 −1.560 −1.580 −1.254 −1.386 −0.528 Serping1 −0.287 −0.559 −0.476 −0.077 −0.527 −0.712 Fn1 −0.524 −1.030 −0.711 −0.869 −0.680 −0.120 Lrp1 −0.638 −0.730 −0.779 −0.663 −0.837 −0.329 Animal Number 46 47 48 37 38 39 Toxicant Carbon Carbon Carbon Bromobenzene Bromobenzene Bromobenzene Tetrachloride Tetrachloride Tetrachloride Dose (mg/kg) 200 200 200 785 785 785 Inflammation 0 0 0 1 1 2 Vacuolation 4 3 3 2 3 3 Bile Duct Hyperplasia 0 0 0 0 0 0 and Fibroplasia Cytoplasmic Alteration 0 1 2 1 2 3 Necrosis 1 0 1 0 0 3 Gapdh 2608 2613.3 2661.3 2931.8 2799.3 2968.3 Hprt1 735.3 656 561.5 1715 1739.5 1380 Ppib 1972.8 1801.5 1853.8 1675.5 1900 1655.3 A2m −2.891 −2.439 −5.167 −4.054 −4.444 −2.844 Cxcl1 −0.500 −0.165 −0.462 −0.610 −0.492 −0.386 RT1-DMa 0.711 0.673 1.089 −0.569 −0.589 0.149 Arf6 0.172 0.167 0.214 0.324 0.475 0.461 Dsc2 −0.280 −0.204 −0.265 0.800 0.827 0.610 Sod2 0.009 −0.014 −0.116 0.200 −0.035 0.134 Cxcl16 1.782 1.992 1.656 −0.140 −1.150 −0.275 Lame2 2.130 2.338 1.341 −0.725 −1.692 −0.854 Ccl2 1.662 2.378 1.370 −0.790 −1.244 −1.328 Col5a2 2.330 2.442 2.138 −0.708 −0.778 −0.542 Arrb1 2.288 2.226 1.692 −1.220 −1.482 −0.627 Vhl 2.626 2.628 2.130 0.043 −0.096 −0.334 Ctgf 2.232 2.664 1.663 −1.387 −1.037 −0.649 Len2 0.356 1.528 2.126 −0.682 −0.719 −0.661 Lbp 0.379 0.665 0.050 0.157 0.036 0.207 S100A11 0.421 0.731 0.599 −0.356 −0.292 0.061 Pkm2 0.586 0.642 0.663 −0.142 −0.085 0.069 TagIn2 0.282 0.110 0.153 −0.669 −0.625 0.147 Cyba 0.799 0.888 0.887 −0.761 −0.590 0.049 Capg 0.855 0.909 0.968 −0.835 −0.762 0.053 C1qb 0.290 0.085 0.332 −0.465 −0.014 0.309 Plau 0.765 0.947 0.720 −1.049 −0.402 −0.470 Fstl1 0.017 −0.180 0.025 −1.078 −0.899 −0.423 Vim 0.004 0.348 0.360 −0.148 −0.045 −0.109 Col4a1 −0.024 −0.441 0.104 −0.512 −0.387 −0.163 Fbn1 0.230 −0.294 0.107 −1.303 −1.090 −0.632 Nid1 0.232 0.186 0.154 −0.460 −0.132 0.014 Col1a1 1.411 1.309 1.774 −0.659 −0.336 0.149 Lgals1 0.978 1.986 1.602 −0.856 −0.388 −0.455 Arpc1b 1.145 1.554 1.382 −0.171 −0.454 −0.337 CD53 1.094 1.315 1.262 −0.045 −0.339 0.303 Itgb2 0.502 0.455 0.302 −0.722 −0.914 −0.301 Itga1 0.585 0.503 0.756 −0.672 −0.525 0.257 RT1-Da 0.918 1.213 1.280 −0.205 −0.563 0.533 Lgals3bp 0.486 0.360 0.302 −0.415 −0.105 0.126 Pcolce 0.354 0.651 −0.401 −1.230 −0.974 −0.145 CP −0.328 −0.317 −0.414 −1.055 −0.969 −0.530 Igfbp2 1.416 0.505 −1.839 0.339 0.249 −0.180 CD9 −0.103 0.754 −0.347 −0.072 −0.052 0.416 Serpine1 −0.345 0.467 −0.524 0.153 0.825 −0.550 Lox −0.493 0.022 0.077 −1.197 −1.023 −0.699 Plod2 −0.357 −0.045 −0.258 −0.446 −0.410 −0.613 Plat −0.411 −0.289 −0.385 0.202 0.005 0.027 Slc25a24 −0.511 −0.262 −0.615 −0.143 0.149 0.189 Fam102b −0.140 −0.011 −0.240 −0.808 −0.338 −0.148 Col1a2 0.458 0.329 0.672 −0.901 −0.686 −0.378 Fxyd5 0.404 0.507 0.213 −0.189 −0.159 0.283 Fam105a 0.576 0.985 0.758 −0.461 −0.047 0.188 Timp1 1.200 1.645 1.241 −0.428 −0.191 −0.231 S100A6 −0.686 0.408 −0.019 −0.521 0.005 −0.682 Lgals3 1.444 2.024 1.736 1.367 0.936 1.432 Gpnmb 2.232 3.101 2.714 1.906 1.987 2.373 Anxa2 0.586 0.834 0.587 1.771 1.226 1.391 Lum −0.201 0.404 0.442 −0.152 −0.296 −0.116 Mmp2 0.311 0.610 −0.241 −0.086 0.177 0.235 Igfbp1 0.070 0.480 −0.925 3.275 3.897 0.758 Cyp2c11 −3.301 −0.339 −0.904 −7.760 −8.696 −7.411 Angptl3 −1.071 −0.753 −0.775 −0.864 −1.104 −0.499 Apoc −0.356 −0.337 −0.414 −0.325 −0.372 −0.172 Vtn −0.381 −0.494 −0.473 −1.353 −1.261 −0.746 Tgfb1 0.107 −0.102 −0.395 −0.596 −0.528 −0.330 Igfbp3 0.063 −0.304 −0.113 −2.127 −1.911 −1.316 Cxcl12 0.320 0.041 0.403 −2.564 −2.540 −1.640 Igfals −0.092 −0.771 −0.189 −2.524 −2.336 −2.083 Serping1 −0.714 −0.546 −0.514 −1.107 −0.925 −0.627 Fn1 −0.152 −0.364 −0.262 −1.880 −1.522 −1.313 Lrp1 −0.337 −0.524 −0.671 −1.297 −1.003 −0.323 Animal Number 40 65 66 67 68 Toxicant Bromobenzene Dexamethasone Dexamethasone Dexamethasone Dexamethasone Dose (mg/kg) 785 1 1 1 1 Inflammation 1 0 0 0 0 Vacuolation 1 0 0 0 0 Bile Duct Hyperplasia 0 0 0 0 0 and Fibroplasia Cytoplasmic Alteration 1 4 4 4 4 Necrosis 0 1 1 1 3 Gapdh 2811 2151.5 1813.3 2471 3013.3 Hprt1 1716 324.3 278.5 478.5 537.5 Ppib 1677.3 1332.3 982.3 1040 1524.8 A2m −1.670 −1.370 −0.649 −0.615 −0.252 Cxcl1 −0.930 0.104 1.127 0.364 0.097 RT1-DMa −0.606 3.152 2.497 3.371 2.417 Arf6 0.239 −0.268 −0.346 −0.401 0.005 Dsc2 0.624 −0.209 −0.593 −0.466 −0.248 Sod2 0.187 −0.398 −0.428 −0.371 −0.367 Cxcl16 −0.468 −0.555 −0.537 −4.885 0.714 Lame2 −1.188 −0.132 0.260 −1.038 0.536 Ccl2 −1.622 −0.272 0.250 0.043 1.019 Col5a2 −0.877 −0.407 −0.910 −2.382 0.311 Arrb1 −2.254 −0.840 −2.152 −3.043 0.703 Vhl −0.363 −0.300 −1.037 −0.787 0.504 Ctgf −0.389 −0.755 0.747 −0.663 0.405 Len2 −1.007 −0.470 0.418 0.883 0.535 Lbp −0.066 0.344 −0.042 0.261 −0.020 S100A11 −0.441 −0.377 −0.570 −0.732 −0.465 Pkm2 −0.110 −0.668 −0.611 −0.735 −0.472 TagIn2 −0.816 −0.486 −0.918 −0.563 −0.566 Cyba −0.752 −0.998 −1.793 −1.244 −0.956 Capg −1.140 −0.558 −0.744 −0.772 −0.404 C1qb 0.018 −0.174 −0.655 −0.257 −0.222 Plau −1.553 −0.719 −2.088 −1.424 −0.095 Fstl1 −1.140 −1.085 −1.346 −1.183 −0.931 Vim −0.327 −1.514 −0.856 −1.292 −1.277 Col4a1 −0.340 −1.039 −1.035 −1.397 −0.880 Fbn1 −1.013 −1.213 −1.784 −2.160 −1.736 Nid1 −0.579 −1.271 −1.374 −1.271 −1.155 Col1a1 −0.231 −4.640 −3.775 −5.473 −0.928 Lgals1 −0.084 0.458 −4.140 −0.346 0.583 Arpc1b −0.315 −1.391 −2.770 −5.994 −0.172 CD53 −0.440 −0.716 −3.901 −5.862 0.006 Itgb2 −1.032 −1.330 −2.265 −1.982 −0.802 Itga1 −0.880 −2.088 −3.379 −2.849 −1.903 RT1-Da −0.554 −4.927 −7.563 −4.272 −3.443 Lgals3bp −0.427 −1.477 −0.782 −1.281 −0.669 Pcolce −1.087 −1.293 −1.196 −1.572 −0.246 CP −1.250 −0.134 −0.634 −0.952 −0.558 Igfbp2 0.559 −0.258 −0.949 −1.156 −0.041 CD9 0.476 0.155 −0.656 −0.280 0.387 Serpine1 0.552 0.251 1.560 0.110 0.038 Lox −0.615 0.278 0.412 −0.164 1.170 Plod2 −0.623 −0.065 0.269 −0.568 −0.077 Plat 0.084 0.103 0.075 −0.461 −0.335 Slc25a24 −0.325 −0.387 −0.212 −0.565 −0.427 Fam102b −0.780 −0.462 −0.124 −0.822 −0.262 Col1a2 −0.731 −0.960 −1.057 −2.208 −1.081 Fxyd5 −0.184 −0.247 −0.412 −0.151 −0.305 Fam105a −0.207 −0.295 0.195 −0.809 −0.294 Timp1 −0.056 0.026 0.464 −0.134 1.004 S100A6 0.207 0.650 −0.047 0.843 0.695 Lgals3 0.867 0.011 0.320 0.370 0.526 Gpnmb 1.454 −0.018 1.304 0.968 1.447 Anxa2 0.783 0.519 0.194 −0.132 0.293 Lum −0.530 0.593 0.401 −0.997 −0.078 Mmp2 −0.151 −0.245 −1.273 −0.990 −0.583 Igfbp1 3.616 1.132 1.740 0.780 0.489 Cyp2c11 −6.882 0.259 0.532 −0.332 0.252 Angptl3 −0.518 −0.276 0.029 −0.467 −0.241 Apoc −0.338 −0.250 −0.067 −0.469 −0.542 Vtn −0.854 −0.111 −0.294 −0.579 −0.572 Tgfb1 −0.639 −1.193 −1.526 −1.328 −1.429 Igfbp3 −1.713 −1.125 −1.454 −2.523 −1.663 Cxcl12 −2.717 −1.808 −3.742 −2.144 −1.869 Igfals −3.007 −0.678 −2.820 −1.013 −1.310 Serping1 −0.678 0.154 0.026 −0.228 0.065 Fn1 −1.481 0.397 0.181 −0.334 −0.170 Lrp1 −1.011 −0.206 −0.631 −0.863 −0.371

The expression patterns of the genes measured by the Bioplex multiplexed assay correlated positively with the expression patterns reported in the DrugMatrix database (R2=0.79; FIG. 7). The average log-ratio versus control across all samples showing fibrosis for genes on the Bioplex assay was well correlated with Drug Matrix.

Differential gene expression was analyzed by hierarchical biclustering with the fibrogenic chemicals (all dose groups) (FIG. 8). Of the 67 genes available for analysis on the panel, fibrogenic chemicals causing fibrosis clustered separately on the y-axis, with the exception of two allyl alcohol-treated animals. Toxicant-dose groups with the fibrosis phenotype clustered separately from the vacuolation and glycogen accumulation phenotypes (FIG. 8). Carbon tetrachloride (the delayed-onset fibrogenic chemical) clustered mid-way between non-fibrogenic and fibrogenic doses of the other fibrogenic chemicals. Gene expression profiles for two allyl alcohol exposures with the fibrosis phenotype clustered with the non-fibrogenic chemical-dose groups. A third localized on the border between fibrogenic and nonfibrogenic clusters. All other fibrogenic chemical-dose groups with fibrosis clustered together. All of the fibrosis-positive animals dosed with 4,4′-methylenedianiline clustered together (FIG. 8).

Chemical-dose groups causing fibrosis produced more differential gene expression of the genes in the panel than chemical-dose groups without fibrosis (FIG. 9). The difference was most pronounced in upregulated genes (FIG. 9). For non-fibrogenic bromobenzene and dexamethasone, 12 genes were downregulated in the chemicals causing fatty accumulation profiles and upregulated in fibrogenic chemical-dose groups (>+1.5-fold [average] above dashed lines in FIG. 9 and Table 3; Col1a1, Col1a2, Col4a1, Cp, Cyba, Fbn1, Itgal, Itgb2, Pcolce, Plau, Lamac2, and RT1-Da). Of the 67 genes on the final panel, 19 were <+1.5-fold expression (FIG. 9; Table 2). Only one gene was significantly downregulated in the non-fibrosis chemical-dose group (A2m; a-2 macroglobulin). Expression of 51 out of the 67 genes (76% of the panel) was ±1.5-fold control expression for fibrogenic compounds with histopathological evidence of fibrosis (Table 2). Only one gene (1.5%) was +1.5-fold control expression for fibrogenic compounds without histopathological evidence of fibrosis (A2m). Panel gene expression of the carbon-tetrachloride dose group was mid-way between fibrosis-positive chemical-dose groups and non-fibrogenic chemical-dose groups (FIG. 9). Non-fibrogenic compounds induced differential expression in 33 out of the 67 genes (50% of the panel). Of these, expression was anti-correlated with fibrogenic, fibrosis-positive cohorts.

Four of the genes included on the panel (Lcn2, A2m, Pcolce, and Lbp) were part of a co-expression module including A2m, the gene encoding a protein used in the Fibrosure test for fibrosis or steatohepatitis. These differentially expressed genes showed an expression pattern unique to the fibrosis phenotype and fibrogenic chemical classification (FIG. 10). Three of the genes (A2m, Lcn2, and Pcolce) were downregulated for bromobenzene (nonfibrogenic, vacuolation) relative to the other pathologies (Table 2). Pcolce expression levels induced by dexamethasone and bromobenzene (nonfibrogenic with lipid-associated pathologies) were anti-correlated with corresponding gene expression levels induced by 4,4′-methylenedianiline and allyl alcohol (fibrogenic compounds) (Table 3).

TABLE 3 Anti-correlated signature genes* Gene Fibrogenic Mechanistic Category Col1a1 Fibrosis and ECM deposition/degradation Col1a2 Fibrosis and ECM deposition/degradation Col4a1 Fibrosis and ECM deposition/degradation Cp Inflammation/chemotaxis Cyba Xenobiotic metabolism Fbn1 Inflammation/chemotaxis Itgal Inflammation/chemotaxis Itgb2 Inflammation/chemotaxis Lamac2 Inflammation/chemotaxis RT1-Da Inflammation/chemotaxis Pcolce Fibrosis and ECM deposition/degradation Plau Fibrosis and ECM deposition/degradation *downregulated in nonfibrogenic chemicals and upregulated in fibrogenic chemicals with fibroplasia; ECM, extracellular matrix

Differentially expressed genes in the fibrogenic signature gene panel were categorized into the following mechanistic groups based on a review of the literature for each gene: hyperplasia, fibrosis and extracellular matrix degradation, inflammatory signaling/chemotaxis, xenobiotic metabolism, and contractility (FIG. 11). Twelve genes upregulated above control expression by at least 1.5-fold in the fibrosis-inducing chemical-dose groups showed the opposite expression pattern in the non-fibrogenic chemical-dose groups (Table 2 and FIGS. 8 and 10). These genes were associated with multiple mechanistic categories of fibrosis, including inflammation and chemotaxis, extracellular matrix deposition/degradation, xenobiotic metabolism (FIG. 11). None of the anti-correlated genes associated with hyperplasia or contractility (FIG. 11; Table 3).

The human orthologs of the rodent genes are presented below in Table 4.

TABLE 4 Rat genes included in the diagnostic test for fibrosis, and human orthologs thereof Rat Human ortholog No. Name Gene symbol Gene Id Gene symbol Gene Id 1 alpha-2-macroglobulin A2m 24153 A2M 2 2 angiopoietin-like 3 Angptl3 502970 ANGPTL3 27329 3 annexin A2 Anxa2 56611 ANXA2 302 4 apolipoprotein E Apoe 25728 APOE 348 5 ADP-ribosylation factor 6 Arf6 79121 ARF6 382 6 actin related protein 2/3 Arpc1b 54227 ARPC1B 10095 com 7 arrestin, beta 1 Arrb1 25387 ARRB1 408 8 complement component 1, q Clqb 29687 ClQB 713 9 capping protein (actin Capg 297339 CAPG 822 filamen 10 chemokine (C-C motif) Ccl2 24770 CCL2 6347 ligan 11 Cd53 molecule Cd53 24251 CD53 963 12 CD9 molecule Cd9 24936 CD9 928 13 collagen, type I, alpha 1 Col1a1 29393 COL1A1 1277 14 collagen, type I, alpha 2 Col1a2 84352 COL1A2 1278 15 collagen, type IV, alpha 1 Col4a1 290905 COL4A1 1282 16 collagen, type V, alpha 2 Col5a2 85250 COL5A2 1290 17 ceruloplasmin (ferroxidase) Cp 24268 CP 1356 18 connective tissue growth fac Ctgf 64032 CTGF 1490 19 chemokine (C—X—C motif) Cxcl1 81503 CXCL1, CXCL3 2919, liga 292 20 chemokine (C—X—C motif) Cxcl12 24772 CXCL12 6387 liga 21 chemokine (C—X—C motif) Cxcl16 497942 CXCL16 58191 liga 22 cytochrome b-245, alpha Cyba 79129 CYBA 1535 pol. 23 cytochrome P450, Cyp2c11 29277 CYP2C18 1562 subfamily 24 desmocollin 2 Dsc2 291760 DSC2 1824 25 family with sequence Fam102b 365903 FAM102B 284611 similar 26 family with sequence Fam105a 310190 FAM105A 54491 similar 27 fibrillin 1 Fbn1 83727 FBN1 2200 28 fibronectin 1 Fn1 25661 FN1 2335 29 follistatin-like 1 Fstl1 79210 FSTL1 11167 30 FXYD domain-containing Fxyd5 60338 FXYD5 53827 ion 31 glycoprotein (transmembran Gpnmb 113955 GPNMB 10457 32 insulin-like growth factor Igfals 79438 IGFALS 3483 bind 33 insulin-like growth factor Igfbp1 25685 IGFBP1 3484 bind 34 insulin-like growth factor Igfbp2 25662 IGFBP2 3485 bind 35 insulin-like growth factor Igfbp3 24484 IGFBP3 3486 bind 36 integrin, alpha L Itgal 308995 ITGAL 3683 37 integrin, beta 2 Rgb2 309684 ITGB2 3689 38 laminin, gamma 2 Lamc2 192362 LAMC2 3918 39 lipopolysaccharide binding p Lbp 29469 LBP 3929 40 lipocalin 2 Lcn2 170496 LCN2 3934 41 lectin, galactoside-binding, s Lgals1 56646 LGALS1 3656 42 lectin, galactoside-binding, s Lgals3 83781 LGALS3 3958 43 lectin, galactoside-binding, s Lgals3bp 245955 LGALS3BP 3959 44 lysyl oxidase Lox 24914 LOX 4015 45 low density lipoprotein Lrp1 299858 LRP1 11; I recep 46 lumican Lum 81682 LUM 4060 47 matrix metallopeptidase 2 Mmp2 81686 MMP2 4313 48 nidogen 1 Nid1 25494 NID1 4811 49 procollagen C-endopeptidase Pcolce 29569 PCOLCE 5118 50 pyruvate kinase, muscle Pkm 25630 PKM 5315 51 plasminogen activator, Plat 25692 PLAT 5327 tissue 52 plasminogen activator, Plau 25619 PLAU 5328 urokin 53 procollagen lysine, 2- Plod2 300901 PLOD2 5352 oxoglut 54 RT1 class II, locus Da RT1-Da 294269 HLA-DRA 3122 55 RT1 class II, locus DMa RT1- 294274 HLA-DMA 3108 DMa 56 S100 calcium binding S100a11 445415 S100A11 6282 protein 57 S100 calcium binding S100a6 85247 S100A6 6277 protein 58 serpin peptidase inhibitor, Serpine1 24617 SERPINE1 5054 cla 59 serpin peptidase inhibitor, Serping1 295703 SERPING1 710 cla 60 solute carrier family 25 Slc25a24 310791 SLC25A24 29957 (mito 61 superoxide dismutase 2, mit Sod2 24787 SOD2 6648 62 transgelin 2 Tagln2 304983 TAGLN2 8407 63 transforming growth factor, b Tgfbl 116487 TGFBl 7045 64 TIMP metallopeptidase Timp1 115510 TIMP1 7076 inhibi 65 von Hippel-Lindau tumor Vhl 24874 VHLL 391104 sup 66 vimentin Vim 81818 VIM 7431 67 vitronectin Vtn 29169 VTN 7448 Classifier for Predicting Fibrosis Development

The gene panel tested in the Group 1 experimental animals was used as the training data set to build a classifier for predicting fibrosis. Only genes present in both microarray and Bioplex data sets were used to build the classifier (59 of 62 genes). Of the 77 available samples, 19 were classified as true positives and 58 were classified as true negatives by histopathology. The internal cross-validation estimate of error rate was 2.6 for the training data set (Table 5). Random forest was used to identify the top genes that contribute most to the classifier performance (Table 5; FIGS. 1A-1F). The random forest classifier was tested using the Bioplex data set. Of the 35 total animal exposures, 13 exposures produced fibrosis with a histopathology score greater than 2 (true positives) and 22 exposures produced no fibrosis by histopathology (true negatives). The accuracy of prediction was 88.6% (Table 5). Area under the receiver operator curve (ROC) was 0.88 for the test set of data. (Ippolito D L, et. al. Gene expression patterns associated with histopathology in toxic liver fibrosis. Tox Sci. 2015 Sep. 22. pii: kfv214)

TABLE 5 Random forest classifier model predictions: training (Group 1) and testing Group (2) sets of experimental animals and data Sensitivity Specificity Accuracy Kappa Training (Microarray)* 94.7 98.3 97.4 0.93 Testing (Bioplex) 69.2 100.0 88.6 0.74 *internal cross-validation (estimate of error rate): 2.6 Protein Expression in the Plasma

Four of the genes included on the panel (Lcn2, A2m, Pcolce, and Lbp) were part of a co-expression module including A2m, the gene encoding a protein used in the Fibrosure test for fibrosis or steatohepatitis (Rossi et al., 2003). The differentially expressed genes showed an expression pattern unique to the fibrosis phenotype and fibrogenic chemical classification (FIG. 13A). Pcolce was the most differentially expressed gene in the fibrosis cohorts (FIG. 13A). Pcolce expression levels induced by dexamethasone and bromobenzene were anti-correlated with corresponding gene expression levels induced by 4,4′-methylenedianiline and allyl alcohol (both fibrogenic compounds) (FIG. 13A). The protein product of Pcolce was significantly and dose-dependently upregulated in plasma in animals dosed with fibrogenic chemicals relative to non-fibrogenic chemicals (FIG. 13B). (Ippolito D L, et. al. Gene expression patterns associated with histopathology in toxic liver fibrosis. Tox Sci. 2015 Sep. 22. pii: kfv214)

Global semiquantitative proteomics analysis (iTRAQ analysis) identified protein products of a subset of the 24 genes differentially expressed in liver tissue specific for the fibrosis phenotype (Table 6). Six protein products were identified in plasma, four in the serum, and two in the liver tissue (Table 6). All protein products were identified in the contrast analysis as specific for the fibrosis phenotype. The direction of the changes in protein products matched the transcriptomics data with the exception of insulin-like growth factor binding protein complex acid labile subunit precursor. This protein was decreased in expression in plasma but the genes Igfbp1 and Igfbp2 were upregulated in liver tissue. (Ippolito D L, et. al. Gene expression patterns associated with histopathology in toxic liver fibrosis. Tox Sci. 2015 Sep. 22. pii: kfv214)

TABLE 6 Fold changes in tissue, plasma, or serum protein abundance measured by iTRAQ mass spectrometry (Group 2) Fold Protein* GI # p** change*** Plasma: fibronectin precursor 186972114 <0.0001 −1.3 ceruloplasmin isoform 1 401461786 <0.0001 2.5 precursor vitronectin precursor 162287178 <0.0001 −1.6 insulin-like growth 71896592 <0.0001 −1.4 factor-binding protein complex acid labile subunit precursor alpha-2-macroglobulin 158138551 0.0370 2.2 precursor Serum: vitronectin precursor 162287178 1.0000 −1.1 ceruloplasmin isoform 1 401461786 <0.0001 2.4 precursor alpha-2-macroglobulin 158138551 <0.0001 2.4 precursor complement C1q 9506433 0.5700 1.6 subcomponent subunit B precursor Tissue: fibronectin precursor 186972114 <0.0001 1.4 ceruloplasmin isoform 1 401461786 <0.0001 3.0 precursor *Rattus norvegicus; **p: p-value, Kruskal Wallis Analysis of Variance by Ranks; ***fold change (4,4′-methylenedianiline/vehicle) Categorization of Fibrogenic Signature Gene Panel

Differentially expressed genes in the fibrogenic signature gene panel were categorized into the following mechanistic groups based on a review of the literature for each gene: hyperplasia, fibrosis and extracellular matrix degradation, inflammatory signaling/chemotaxis, xenobiotic metabolism, and contractility (FIGS. 13A and 13B). Twelve genes upregulated above control expression by at least 1.5-fold in the fibrosis-inducing compound-dose groups showed the opposite expression pattern in the non-fibrogenic compound-dose groups (Group 2 Bioplex experimental animals; FIGS. 13A and 13B). These genes were associated with multiple mechanistic categories of fibrosis, including inflammation and chemotaxis, and extracellular matrix deposition/degradation (FIGS. 13A and 13B). None of the anti-correlated genes were associated with hyperplasia or contractility (FIGS. 13A and 13B). (Ippolito D L, et. al. Gene expression patterns associated with histopathology in toxic liver fibrosis. Tox Sci. 2015 Sep. 22. pii: kfv214)

miRNA Expression in Serum Corroborates Transcription Data in Liver Tissue

Serum miRNA expression was measured by next-generation sequencing. Gene expression in the liver was determined by microarray, and global serum and liver protein expression was determined by semi-quantitative mass spectrometry. We identified 16 differentially expressed miRNA in 4,4′-MDA-treated rats (12 upregulated, including miR-182, miR-122-5p, and -3p; 4 downregulated, including miR-340-5p and miR-182; FDR<0.05; FIG. 12). Transcriptomic analysis identified 506 differentially expressed genes in the liver. 13 miRNAs were predicted to target 100 unique differentially expressed genes in the liver. Global proteomics analysis identified 131 differentially expressed proteins in the liver and 53 in the serum. Of these, 7 miRNAs targeted 13 unique genes coding for differentially expressed liver tissue proteins and 3 miRNAs targeted 3 unique genes coding for serum proteins. These 16 differentially expressed miRNAs in the serum are predicted to target and potentially regulate gene expression contributing to the progression of toxic liver injury. (Fermenter M G et al. Serum miRNA as prognostic indicators of toxic liver injury. Submitted abstract in October 2015 for presentation at the Society of Toxicology in March 2016 (New Orleans, La.)).

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The invention claimed is:
 1. An array comprising a substrate and twenty-five or more first target oligonucleotides and no more than 74 target oligonucleotides in total, each first target oligonucleotide being immobilized on the substrate and specifically hybridizable to mRNA of, cDNA of, or miRNA against a different gene selected from the group consisting of Lcn2; Gpnmb; Lgals3; S100a11; Anxa2; Lbp; Col1a1; Cxcl16; Timp1; Plat; RT1-DMa; Cd9; Lgals1; Tagln2; RT1-Da; Capg; Pkm2; Ccl2; Serpine1; Serping1; Cyba; Fam105a; Cxcl1; Vim; C1qb; Pcolce; Fxyd5; Arpc1b; Pkm; S100a6; Plau; Itgal; Plod2; Ctgf; Col1a2; Igfbp2; Lox; Dsc2; Fam102b; CD53; Itgb2; Lamc2; Cp; Slc25a24; Fbn1; Col4a1; Sod2; Cyp2c11; Igfbp3; Cxcl12; Angptl3; Igfals; Lrp1; Tgfb1; Vtn; Vhl; and mammalian orthologs thereof.
 2. The array of claim 1, wherein the first target oligonucleotides are labelled with a detectable label.
 3. The array of claim 1, wherein the first target oligonucleotides comprise cDNA-specific sequences that each comprise at least one nucleotide difference from corresponding genomic DNA.
 4. The array of claim 2, wherein the detectable label is directly detectable.
 5. The array of claim 2, wherein the detectable label comprises biotin.
 6. The array of claim 5, wherein streptavidin-conjugated phycoerythrin (SAPE) is bound to the biotin.
 7. The array of claim 1, wherein the first target oligonucleotide is immobilized on the substrate due to binding with a capture probe.
 8. A kit for the diagnosis of liver disease, comprising the array according to claim
 1. 9. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 1. 10. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 2. 11. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 3. 12. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 4. 13. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 5. 14. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 6. 15. A method comprising contacting a biological sample from a mammalian subject with the array of claim
 7. 16. A method comprising contacting a biological sample from a subject suspected of having a liver disease with the array of claim
 8. 17. The method of claim 9, wherein the biological sample comprises a cell.
 18. The method of claim 10, wherein the biological sample comprises a cell.
 19. The method of claim 9, wherein the biological sample comprises mRNA.
 20. The method of claim 9, wherein the biological sample comprises cDNA. 